Alternatives to Gemini 3.8 Live

Compare Gemini 3.8 Live alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Gemini 3.8 Live in 2026. Compare features, ratings, user reviews, pricing, and more from Gemini 3.8 Live competitors and alternatives in order to make an informed decision for your business.

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    Gemini Enterprise Agent Platform
    Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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    Gemini

    Gemini

    Google

    Gemini is Google’s advanced AI assistant designed to help users think, create, learn, and complete tasks with a new level of intelligence. Powered by Google’s most capable models, including Gemini 3, it enables users to ask complex questions, generate content, analyze information, and explore ideas through natural conversation. Gemini can create images, videos, summaries, study plans, and first drafts while also providing feedback on uploaded files and written work. The platform is grounded in Google Search, allowing it to deliver accurate, up-to-date information and support deep follow-up questions. Gemini connects seamlessly with Google apps like Gmail, Docs, Calendar, Maps, YouTube, and Photos to help users complete tasks without switching tools. Features such as Gemini Live, Deep Research, and Gems enhance brainstorming, research, and personalized workflows. Available through flexible free and paid plans, Gemini supports everyday users, students, and professionals across devices.
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    Gemini 3.6 Flash
    Gemini 3.6 Flash is Google’s newest Flash model built for efficient, reliable, production-scale AI agents. The model improves on Gemini 3.5 Flash with stronger coding, knowledge work, multimodal performance, computer use, and agentic workflow execution. Gemini 3.6 Flash is designed to use fewer output tokens, take fewer reasoning steps, reduce unnecessary tool calls, and lower the cost of complex AI tasks. It supports document parsing, chart analysis, data analysis, report drafting, code migrations, visual understanding, and multi-agent orchestration. The model is available through the Gemini API, Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise app, and the Gemini app. Built for developers and enterprises, Gemini 3.6 Flash helps teams build faster, lower-cost, and more capable AI agents across coding, analysis, productivity, and multimodal workloads.
    Starting Price: $1.50 per 1M tokens (input)
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    Gemini 3.5 Pro
    Gemini 3.5 Pro is Google’s anticipated next-generation Pro model in the Gemini 3.5 series, designed for advanced reasoning, coding, multimodal understanding, and agentic workflows. It is expected to build on Google’s Gemini 3 family with stronger performance for complex tasks that require planning, context handling, tool use, and deep problem solving. The model is aimed at users who need more power than faster Flash models for demanding development, research, automation, and enterprise AI use cases. Gemini 3.5 Pro is expected to support sophisticated workflows across text, code, files, multimodal inputs, and connected tools. Developers and organizations will likely use it through Google’s AI platforms for building assistants, agents, coding tools, analysis systems, and productivity applications. As an upcoming Pro-tier model, Gemini 3.5 Pro is positioned for high-value workloads where accuracy, reasoning quality, and advanced task execution matter more than maximum speed.
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    Gemini 3.5 Flash
    Gemini 3.5 Flash is Google’s latest frontier AI model designed to combine advanced intelligence, high-speed performance, and agentic workflow execution for developers, enterprises, and everyday users. Built as part of the Gemini 3.5 family, the model excels at coding, long-horizon reasoning, multimodal understanding, and complex multi-step automation tasks while delivering significantly faster output speeds than many competing frontier models. Gemini 3.5 Flash powers AI agents capable of planning, executing, and managing workflows such as application development, codebase maintenance, data analysis, and financial document preparation through the Antigravity harness. The model also supports rich multimodal experiences by generating interactive graphics, dynamic web interfaces, animations, and advanced visual content. Gemini 3.5 Flash is integrated across Google products including the Gemini app, Google Search AI Mode, Google Antigravity, Google AI Studio, Android Studio, and more.
    Starting Price: $1.50 per 1M tokens (input)
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    Gemini Omni Flash
    Gemini Omni is Google’s new model family where Gemini’s ability to reason meets the ability to create, starting with video. The first model in the family, Gemini Omni Flash, can create anything from any input by combining images, audio, video, and text as input, then generating high-quality videos grounded in Gemini’s real-world knowledge. It gives users an easier way to edit video through conversation, where every instruction builds on the last, characters stay consistent, physics hold up, and the scene remembers what came before. Users can transform specific details or entire worlds, reimagine action, add new characters or objects, change environments, adjust camera angles, refine styles, and build multi-turn edits without losing the thread of the original scene. Gemini Omni is designed to bridge photorealism and meaningful storytelling by reasoning about what should happen next, using an intuitive understanding of forces like gravity, kinetic energy, and fluid dynamics.
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    Cartesia Sonic-3.5
    Sonic 3.5 is Cartesia’s fastest, most natural text-to-speech model, built for expressive, real-time voice generation with sub-90ms latency and native support for 42 languages. It is designed to follow transcripts faithfully, voice confirmation codes, and heteronyms correctly without preprocessing, and stay expressive enough to carry a real conversation. It supports languages intended to deliver native-quality speech. Sonic 3.5 focuses on clean audio across every language and voice, with no artifacts to edit out, making it practical for production voice experiences where quality, speed, and consistency matter. Its expressive conversational delivery provides strong pacing and real emotional range, tuned for support and agent transcripts. Alphanumerics such as order numbers, phone numbers, IDs, and emails are spoken naturally in every language, while context-aware English pronunciation helps words like read, bass, and bow land correctly from the surrounding text.
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    Cartesia Sonic-3.6
    Sonic is a real-time text-to-speech model built for voice agents, combining natural delivery, sub-90ms latency, and native support for more than 40 languages. It is designed to make voice interactions feel effortless, with tone that adjusts to context, consistent pacing, and speech that follows the natural rhythm of conversation. By default, Sonic interprets the emotional subtext of a transcript and calibrates delivery automatically, while non-verbal expressions such as laughter can be inserted directly into the text. The model follows transcripts faithfully, produces clean audio across languages and voices, and handles alphanumeric content such as order numbers, phone numbers, IDs, and email addresses naturally without preprocessing. Context-aware pronunciation helps heteronyms sound correct from surrounding words, while custom pronunciation dictionaries let teams define how proper nouns and domain-specific terms should be spoken.
    Starting Price: $5 per month
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    GPT-Live

    GPT-Live

    OpenAI

    GPT-Live is a new generation of voice models for natural human-AI interaction, now powering ChatGPT Voice. It is built to make talking with AI feel much more like having a real conversation through a full-duplex architecture, meaning it can listen and speak at the same time. During conversations, GPT-Live can show it is paying attention with short acknowledgments like “mhmm” or “yeah,” engage in quick back-and-forth, or stay quiet when the user needs a moment to think. Instead of processing separate turns one after another, GPT-Live continuously processes input while generating output, allowing it to decide many times per second whether to speak, keep listening, pause, interrupt, or invoke a tool. For questions that require web search, deeper reasoning, or more complex work, GPT-Live can delegate to a frontier model behind the scenes and bring the result back into the conversation when it is ready, while still maintaining the flow of the voice interaction.
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    GPT-Live-1
    GPT-Live-1 is one of the two new GPT-Live voice models rolling out to ChatGPT users globally, built to make talking with AI feel much more like having a real conversation. It is powered by a full-duplex architecture, so it can listen and speak at the same time instead of waiting for one rigid turn to end before the next begins. During conversations, GPT-Live-1 can show it is paying attention with short acknowledgments, engage in quick back-and-forth, pause when the user needs a moment to think, or stay quiet when asked to listen. It continuously processes input while generating output, allowing the model to decide many times per second whether to speak, keep listening, pause, interrupt, or invoke a tool. GPT-Live-1 also separates natural interaction from deeper work: when a question requires web search, reasoning, or more agentic capabilities, it can delegate the task to a frontier model behind the scenes and bring the result back when it is ready.
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    GPT-Realtime-2
    GPT-Realtime-2 is OpenAI’s voice model for live interactions where the model can keep the conversation moving while it reasons through requests, calls tools, handles corrections or interruptions, and responds in a way that fits the moment. It is built for a new class of voice apps that feel more natural, respond more intelligently, and take action in real time. GPT-Realtime-2 brings GPT-5-class reasoning to voice experiences, helping agents understand what someone means, track context, recover when a request changes, use tools while the conversation continues, and carry the conversation forward naturally. Developers can enable short preambles like “let me check that” so users know the agent is working, and the model can call multiple tools at once while making actions audible with phrases like “checking your calendar” or “looking that up now.” It also has stronger recovery behavior, longer context for agentic workflows, better retention of specialized terminology, etc.
    Starting Price: $32 per 1M tokens
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    GPT-Realtime-2.1
    GPT-Realtime-2.1 is OpenAI’s reasoning model with tool use for low-latency voice agents and complex speech-to-speech workflows. It updates GPT-Realtime-2 with improved alphanumeric recognition, silence and noise handling, and interruption behavior, helping applications understand spoken code, manage imperfect audio, and respond more naturally when users pause or talk over the agent. Developers can configure reasoning effort to balance deeper thinking against latency and output usage, while strong instruction following helps the model stay aligned with a defined role, tone, and workflow. It accepts and produces both audio and text, can take images as input, and supports function calling so an agent can retrieve information or perform actions during a conversation. The model has a 128,000-token context window, supports up to 32,000 output tokens, and includes reasoning-token support for extended interactions.
    Starting Price: $0.40 per cached input
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    Grok Voice Think Fast 2.0
    Grok Voice Think Fast 2.0 is xAI’s flagship voice model for building real-time assistants, phone agents, and interactive voice systems that stream audio and text bidirectionally over WebSocket. Developers can configure system instructions, high or no reasoning effort, built-in or custom voices, automatic server-side voice activity detection, silence duration, idle re-engagement, playback speed, and session resumption after temporary disconnects. It accepts PCM, G.711 μ-law, G.711 A-law, and Opus audio through JSON or raw binary frames, with configurable PCM sample rates from telephone quality to 48 kHz. It supports more than 20 languages with native-quality accents, automatic language detection, natural responses in the speaker’s language, and seamless code-switching. Language hints and up to 100 key terms improve transcription of regional speech, names, products, codes, addresses, and specialized terminology, while pronunciation replacements correct spoken output.
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    MAI-Voice-2

    MAI-Voice-2

    Microsoft AI

    MAI-Voice-2 is Microsoft AI’s most expressive and natural-sounding text-to-speech model to date, built for production voice experiences where fidelity, language coverage, speaker consistency, and emotional range directly shape the user experience. It is designed for assistants, customer support, audiobooks, accessibility experiences, games, podcasts, courses, simulations, and creator workflows where voice quality must sound natural, fluid, and trustworthy. It expands from English-only support to 15 languages while maintaining naturalness and expressiveness, with support for English, Italian, French, German, Hindi, Spanish, Portuguese, Korean, Chinese, Turkish, Russian, Thai, Dutch, Romanian, and Hungarian. MAI-Voice-2 offers granular emotion control through tags such as sad, whispered, and excited, along with role-based expressive speech for experiences like motivational trainers, sports commentators, or character voices.
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    MAI-Voice-2-Flash
    MAI-Voice-2-Flash is Microsoft AI’s fast, efficient text-to-speech model for high-volume voice experiences where responsiveness is essential. It produces high-fidelity, natural, and expressive speech while preserving the prosody, acoustic quality, human-like rhythm, intonation, and emotional nuance of MAI-Voice-2. The model is optimized for real-time synthesis and runs twice as fast as MAI-Voice-2, making it suitable for voice agents, assistants, interactive applications, call centers, and IVR systems that must respond without noticeable delay. It supports 15 languages across 18 locales and includes a library of licensed, curated voices that can be used immediately. Developers can control speaking style and emotion through SSML, shaping delivery with expressions such as joy, excitement, empathy, sadness, whispering, or shouting to match different conversational situations and brand experiences.
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    Qwen-Audio-3.0-TTS-Flash
    Qwen-Audio-3.0-TTS-Flash is the real-time variant of Qwen-Audio-3.0-TTS, tuned for interactive applications with first-packet latency at the 300 ms level. It supports 16 languages, along with improved fidelity for several Chinese dialects. Across multilingual evaluations, Flash delivers the lowest average WER/CER in the family at 3.87, showing strong intelligibility while preserving speaker identity across diverse languages. Developers can guide delivery with plain-language instructions instead of manually adjusting acoustic parameters, controlling emotion, role, scenario, pace, projection, and tone through simple prompts. Inline tags add precise non-verbal details, making the model well-suited to conversational agents, narration, games, dubbing, and other expressive speech experiences. Voice cloning is designed to work with imperfect reference audio; targeted acoustic simulation suppresses noise and reverberation while retaining the original speaker’s timbre.
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    Qwen-Audio-3.0-TTS-Plus
    Qwen-Audio-3.0-TTS-Plus is the high-quality variant of Qwen-Audio-3.0-TTS, optimized for naturalness and timbre fidelity when output quality matters more than speed. It supports 16 languages, plus improved fidelity for several Chinese dialects. The model delivers strong multilingual intelligibility and ranks first in speaker similarity across all supported languages, helping cloned voices remain recognizable and consistent across linguistic contexts. Developers can direct delivery through ordinary natural-language instructions instead of manually tuning acoustic parameters, controlling emotion, role, scenario, pacing, projection, and tone with simple prompts. Inline tags provide fine-grained control over breaths, laughter, emotional shifts, and other non-verbal details, making the model useful for narration, games, character dialogue, and dubbing.
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    Simba 3.2

    Simba 3.2

    Speechify

    Speechify’s text-to-speech API offers a family of Simba models for real-time voice generation across English, European languages, and broader multilingual use cases. Simba 3.2 is recommended for new English integrations, providing streaming-native synthesis, the lowest time to first byte, richer expressivity than earlier generations, and full support for SSML and emotion control. Simba 3.0 extends streaming-native speech to English, German, Spanish, French, Italian, and Brazilian Portuguese, with language selection handled through the request or voice locale. Simba Multilingual supports 35 locales across 30 languages, including mixed-language content and automatic language detection, while Simba English remains available as a legacy model for compatibility. Developers select a model through one parameter and can switch without changing the rest of the request structure, including voice, format, and SSML settings.
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    Gemini 2.5 Flash Native Audio
    Google has released updated Gemini audio models that significantly expand the platform’s capabilities for natural, expressive voice interactions and real-time conversational AI with the introduction of Gemini 2.5 Flash Native Audio and improved text-to-speech technology. The updated native audio model powers live voice agents that can handle complex workflows, follow detailed user instructions more reliably, and maintain smoother multi-turn conversations by better recalling context from previous turns. It is now available across Google AI Studio,Gemini Enterprise Agent Platform, Gemini Live, and Search Live, enabling developers and products to build interactive voice experiences such as intelligent assistants and enterprise voice agents. In addition to the real-time voice improvements, Google enhanced the underlying Text-to-Speech (TTS) models in the Gemini 2.5 family to offer greater expressivity, tone control, pacing adjustments, and multilingual support.
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    Gemini 3.5 Live Translate
    Gemini 3.5 Live Translate is Google’s latest audio model for live speech-to-speech translation, delivering near real-time translation in more than 70 languages. The model automatically detects multilingual input and generates smooth, natural-sounding translated speech that preserves the speaker’s intonation, pacing, and pitch. Unlike turn-by-turn translation systems that wait for someone to finish speaking before responding, Gemini 3.5 Live Translate processes speech as it streams and generates translated audio continuously, balancing the need for context with the need to stay in sync. It stays only a few seconds behind the speaker throughout a session, helping conversations feel more fluid and natural, without awkward pauses. It is built for multilingual calls, meetings, lessons, broadcasts, live interpretation, dubbing, simultaneous translation, and voice translation applications.
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    Gemini Audio
    Gemini Audio is a set of advanced real-time audio models built on Gemini's architecture, designed to enable natural, fluid voice interaction and expressive audio generation through simple language prompts. It supports conversational experiences where users can speak, listen, and interact with AI in a seamless loop, combining understanding, reasoning, and response generation in audio form. It is capable of both analyzing and generating audio, allowing applications such as speech-to-text transcription, translation, speaker identification, emotion detection, and detailed audio content analysis. They are optimized for low-latency, real-time use cases, making them suitable for live assistants, voice agents, and interactive systems that require continuous, multi-turn dialogue. Gemini Audio also integrates advanced capabilities like function calling, enabling the model to trigger external tools and incorporate real-time data into responses.
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    Gemini 3.1 Flash Live
    Gemini 3.1 Flash Live is Google’s most advanced real-time audio model, designed to deliver natural, reliable, and low-latency voice interactions for the next generation of conversational AI. It is optimized for real-time dialogue, enabling fluid, human-like conversations with improved precision, faster response times, and a more natural rhythm that better reflects how people actually speak. It enhances tonal understanding, allowing it to recognize nuances such as pitch, pace, and emotional cues, and dynamically adapt responses to user intent, including frustration or confusion. Built for both developers and enterprises, it can be accessed through the Gemini Live API in Google AI Studio, as well as integrated into production environments to power voice-first agents capable of handling complex, multi-step tasks at scale. It supports multimodal inputs including text, audio, images, and video, and produces both text and audio outputs, enabling richer, context-aware interactions.
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    Gemini 2.5 Flash TTS
    Gemini 2.5 Flash TTS is the latest text-to-speech (TTS) model variant in Google’s Gemini 2.5 lineup, designed for faster, low-latency speech synthesis with expressive, controllable audio output. It offers significant enhancements in tone versatility and expressivity so that developers can generate speech that better matches style prompts, from storytelling narrations to character voices, with more natural emotional range. It features precision pacing, which allows it to adjust speech tempo based on context, delivering faster sections or slowing for emphasis more accurately according to instructions. It also supports multi-speaker dialogues with consistent character voices for scenarios like podcasts, interviews, or conversational agents, and improved multilingual handling so each speaker’s unique tone and style persist across languages. Gemini 2.5 Flash TTS is optimized for lower latency, making it ideal for interactive applications and real-time voice interfaces.
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    Gemini Flash
    Gemini Flash is an advanced large language model (LLM) from Google, specifically designed for high-speed, low-latency language processing tasks. Part of Google DeepMind’s Gemini series, Gemini Flash is tailored to provide real-time responses and handle large-scale applications, making it ideal for interactive AI-driven experiences such as customer support, virtual assistants, and live chat solutions. Despite its speed, Gemini Flash doesn’t compromise on quality; it’s built on sophisticated neural architectures that ensure responses remain contextually relevant, coherent, and precise. Google has incorporated rigorous ethical frameworks and responsible AI practices into Gemini Flash, equipping it with guardrails to manage and mitigate biased outputs, ensuring it aligns with Google’s standards for safe and inclusive AI. With Gemini Flash, Google empowers businesses and developers to deploy responsive, intelligent language tools that can meet the demands of fast-paced environments.
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    Gemini 2.5 Pro TTS
    Gemini 2.5 Pro TTS is Google’s advanced text-to-speech model in the Gemini 2.5 family, optimized for high-quality, expressive, controllable speech synthesis for structured and professional audio generation tasks. The model delivers natural-sounding voice output with enhanced expressivity, tone control, pacing, and pronunciation fidelity, enabling developers to dictate style, accent, rhythm, and emotional nuance through text-based prompts, making it suitable for applications like podcasts, audiobooks, customer assistance, tutorials, and multimedia narration that require premium audio output. It supports both single-speaker and multi-speaker audio, allowing distinct voices and conversational flows in the same output, and can synthesize speech across multiple languages with consistent style adherence. Compared with lower-latency variants like Flash TTS, the Pro TTS model prioritizes sound quality, depth of expression, and nuanced control.
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    Gemini 4

    Gemini 4

    Google

    Gemini 4 is Google’s next-generation Gemini model family currently in development after the release of Gemini 3.6 Flash and Gemini 3.5 Flash-Lite. Google has confirmed that pre-training for Gemini 4 has begun, positioning it as the company’s most ambitious model training effort yet. The model is expected to advance Google’s frontier AI work across reasoning, coding, multimodal understanding, agentic workflows, and enterprise AI use cases. Because Gemini 4 has not been publicly released yet, official pricing, model cards, benchmarks, API details, and availability have not been published. Gemini 4 follows Google’s broader Gemini strategy of building models for developers, enterprises, consumer apps, and AI-powered products across Google’s ecosystem. Built for the next stage of AI agents and intelligent applications, Gemini 4 is likely to become a major foundation for future Google AI products once it becomes available.
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    Gemini 3.1 Flash TTS
    Gemini 3.1 Flash TTS is Google’s latest text-to-speech model designed to deliver highly expressive, controllable, and scalable AI-generated speech for developers and enterprises. Available in Google AI Studio and Gemini Enterprise Agent Platform, it focuses on precise control over how audio is generated, allowing users to shape delivery through natural language prompts and an extensive system of more than 200 audio tags that define pacing, tone, emotion, and style. It supports over 70 languages and regional variants, along with a library of 30 prebuilt voices, enabling users to generate speech ranging from professional narration to conversational or stylized performances. Developers can embed instructions directly into text inputs to guide vocal expression, combining pacing, emotion, and pauses in a structured prompting framework that produces nuanced, high-fidelity audio output. Gemini 3.1 Flash TTS is optimized for real-world applications.
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    Vision Agents
    Vision Agents is an open source Python framework for building low-latency voice and video AI agents with any model. It lets developers plug in LLM, speech, and vision models from more than 25 providers and ship real-time agents for telehealth, voice support, live coaching, video analysis, interactive avatars, security monitoring, sports commentary, and other multimodal applications. It is designed to help teams build agents that can listen, speak, see, process media, call tools, and respond in real time while running on Stream’s global edge network with sub-500ms latency. Developers can build a first agent in minutes, using a small Python setup with Gemini Realtime, OpenAI, Deepgram, ElevenLabs, Stream, or other supported providers. Vision Agents supports both real-time speech-to-speech models and custom STT/LLM/TTS pipelines, giving teams either the fastest path to a working voice agent or full control over speech recognition, language reasoning, text-to-speech, etc.
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    Gemini 2.5 Flash-Lite
    Gemini 2.5 is Google DeepMind’s latest generation AI model family, designed to deliver advanced reasoning and native multimodality with a long context window. It improves performance and accuracy by reasoning through its thoughts before responding. The model offers different versions tailored for complex coding tasks, fast everyday performance, and cost-efficient high-volume workloads. Gemini 2.5 supports multiple data types including text, images, video, audio, and PDFs, enabling versatile AI applications. It features adaptive thinking budgets and fine-grained control for developers to balance cost and output quality. Available via Google AI Studio and Gemini API, Gemini 2.5 powers next-generation AI experiences.
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    Leadlock

    Leadlock

    Leadlock

    Leadlock is a speech-to-speech voice AI platform built specifically for GoHighLevel agencies, helping them answer every call, qualify leads, book appointments, and update GHL pipelines in real time. Unlike traditional voice AI stacks that chain speech-to-text, an LLM, and text-to-speech, it supports true multimodal speech-to-speech through OpenAI Realtime and Gemini Live, alongside xAI Grok and ElevenLabs options, enabling sub-second latency, natural turn-taking, and interruptions. Agencies can choose from more than 72 voices across multiple providers and select different models for different agents and use cases. Native GoHighLevel integration connects contacts, calendars, pipelines, opportunities, tags, custom fields, workflows, and sub-accounts without middleware or Zapier-style glue. Before answering, agents can pull caller history and CRM context to personalize conversations from the first ring.
    Starting Price: $97 per month
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    Gemini 3 Pro
    Gemini 3 Pro is Google’s most advanced multimodal AI model, built for developers who want to bring ideas to life with intelligence, precision, and creativity. It delivers breakthrough performance across reasoning, coding, and multimodal understanding—surpassing Gemini 2.5 Pro in both speed and capability. The model excels in agentic workflows, enabling autonomous coding, debugging, and refactoring across entire projects with long-context awareness. With superior performance in image, video, and spatial reasoning, Gemini 3 Pro powers next-generation applications in development, robotics, XR, and document intelligence. Developers can access it through the Gemini API, Google AI Studio, or Gemini Enterprise Agent Platform, integrating seamlessly into existing tools and IDEs. Whether generating code, analyzing visuals, or building interactive apps from a single prompt, Gemini 3 Pro represents the future of intelligent, multimodal AI development.
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    Gemini 3.5 Transcribe
    Gemini 3.5 Transcribe is Google’s most precise speech-to-text model yet, designed for intelligent voice interactions and real-time transcription. Instead of simply converting speech word for word, it turns raw audio into accurate, polished, formatted text while handling background noise, complex jargon, accents, dialects, and natural speaking patterns. Smart transcription automatically understands self-corrections, removes filler words such as “ums” and “ahs,” and formats the final text for readability. The model supports continuous bidirectional streaming with sub-second latency for interactive voice applications, as well as pre-recorded audio processing for meetings, call logs, and other recordings with speaker attribution and word-level timestamps. Custom vocabulary helps it recognize specialized terminology, unique spellings, postal codes, order IDs, and other domain-specific language.
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    Gemini 3.1 Pro
    Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows.
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    Gemini Robotics-ER 1.6

    Gemini Robotics-ER 1.6

    Google DeepMind

    Gemini Robotics-ER 1.6 is a family of AI models developed by Google DeepMind to bring advanced multimodal intelligence into the physical world by enabling robots to perceive, reason, and act in real-world environments. Built on the Gemini 2.0 foundation, it extends traditional AI capabilities by adding physical action as an output modality, allowing robots to interpret visual input and natural language instructions and convert them directly into motor commands to complete tasks. It includes a vision-language-action model that processes images and instructions to execute tasks, as well as a complementary embodied reasoning model (Gemini Robotics-ER) that specializes in spatial understanding, planning, and decision-making within physical environments. These models enable robots to generalize across new situations, objects, and environments, allowing them to perform complex, multi-step tasks even if they were not explicitly trained for them.
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    Gemini 3 Flash
    Gemini 3 Flash is Google’s latest AI model built to deliver frontier intelligence with exceptional speed and efficiency. It combines Pro-level reasoning with Flash-level latency, making advanced AI more accessible and affordable. The model excels in complex reasoning, multimodal understanding, and agentic workflows while using fewer tokens for everyday tasks. Gemini 3 Flash is designed to scale across consumer apps, developer tools, and enterprise platforms. It supports rapid coding, data analysis, video understanding, and interactive application development. By balancing performance, cost, and speed, Gemini 3 Flash redefines what fast AI can achieve.
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    Gemini 2.5 Flash Image
    Gemini 2.5 Flash Image is Google’s latest state-of-the-art image generation and editing model, now accessible via the Gemini API, Google AI Studio’s build mode, and Gemini Enterprise Agent Platform. It enables powerful creative control by allowing users to blend multiple input images into a single visual, maintain consistent characters or products across edits for rich storytelling, and apply precise, natural-language-based–based transformations, such as removing objects, changing poses, adjusting colors, or altering backgrounds. The model is backed by Gemini’s deep world knowledge, enabling it to understand and reinterpret scenes or diagrams in context, which unlocks dynamic use cases like educational tutors or scene-aware editing assistants. Demonstrated through customizable template apps in AI Studio (including photo editors, multi-image fusers, and interactive tools), the model supports rapid prototyping and remixing via prompts or UI.
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    Gemini 2.0 Flash-Lite
    Gemini 2.0 Flash-Lite is Google DeepMind's lighter AI model, designed to offer a cost-effective solution without compromising performance. As the most economical model in the Gemini 2.0 lineup, Flash-Lite is tailored for developers and businesses seeking efficient AI capabilities at a lower cost. It supports multimodal inputs and features a context window of one million tokens, making it suitable for a variety of applications. Flash-Lite is currently available in public preview, allowing users to explore its potential in enhancing their AI-driven projects.
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    Gemini 2.0 Flash Thinking
    Gemini 2.0 Flash Thinking is an advanced AI model developed by Google DeepMind, designed to enhance reasoning capabilities by explicitly displaying its thought processes. This transparency allows the model to tackle complex problems more effectively and provides users with clear explanations of its decision-making steps. By showcasing its internal reasoning, Gemini 2.0 Flash Thinking not only improves performance but also offers greater explainability, making it a valuable tool for applications requiring deep understanding and trust in AI-driven solutions.
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    Gemini 3.1 Flash Image
    Gemini 3.1 Flash Image is Google DeepMind’s latest image generation model, combining advanced Pro-level capabilities with lightning-fast performance. It delivers enhanced world knowledge, enabling more accurate subject rendering and data-informed visuals grounded in real-time information. The model improves precision text rendering and in-image translation, making it well-suited for marketing assets, infographics, and localized creative content. Stronger instruction following ensures complex prompts are executed with clarity and accuracy. Gemini 3.1 Flash Image maintains subject consistency across multiple characters and objects within a single workflow. It supports production-ready outputs with customizable aspect ratios and resolutions up to 4K. Available across Gemini, Search, AI Studio, Google Cloud, and more, it brings high-quality visual generation at Flash-level speed.
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    Gemini 3 Deep Think
    The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows.
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    Gemini Nano
    Gemini Nano from Google is a lightweight, energy-efficient AI model designed for high performance in compact, resource-constrained environments. Tailored for edge computing and mobile applications, Gemini Nano combines Google's advanced AI architecture with cutting-edge optimization techniques to deliver seamless performance without compromising speed or accuracy. Despite its compact size, it excels in tasks like voice recognition, natural language processing, real-time translation, and personalized recommendations. With a focus on privacy and efficiency, Gemini Nano processes data locally, minimizing reliance on cloud infrastructure while maintaining robust security. Its adaptability and low power consumption make it an ideal choice for smart devices, IoT ecosystems, and on-the-go AI solutions.
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    Higgs Realtime
    Higgs Realtime is a production-quality, real-time speech-to-speech model and API built for natural, continuous conversation. It is an end-to-end, instruction-tuned, audio-native model that can understand audio, text, or both and generate high-quality responses, while also functioning as a text LLM when given text alone. Designed for live voice agents, it follows conversations, handles interruptions, adapts when requests change mid-sentence, and carries multi-step workflows through to completion. The model is trained specifically for voice-agent reflexes such as natural turn-taking, conversational cadence, tone adaptation, spoken tool preambles, multi-turn state tracking, and robust instruction following through changing requests. Semantic turn detection helps distinguish a completed turn from a pause, while multilingual and code-switched understanding supports more than 100 languages without per-language setup.
    Starting Price: $0.0023 per minute
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    Gemini 3.5 Flash-Lite
    Gemini 3.5 Flash-Lite is Google’s fastest model in the Gemini 3.5 series, designed for low-latency tasks and high-throughput developer workflows such as agentic search, document processing, coding, and large-scale data analysis. It delivers 350 output tokens per second and significantly improves on previous Flash-Lite generations in both quality and agentic performance. Developers can configure its thinking level to match the workload: minimal or low thinking supports fast execution for high-volume tasks, while higher thinking levels enable more complex, multi-step subagent workflows. Built-in computer-use capabilities allow the model to interact reliably with digital environments across supported surfaces. Gemini 3.5 Flash-Lite also advances coding, long-context understanding, and real-world task execution, outperforming Gemini 3.1 Flash-Lite across key evaluations and even surpassing Gemini 3 Flash on several agentic and software-engineering benchmarks.
    Starting Price: $0.30 per 1M input tokens
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    Gemma

    Gemma

    Google

    Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs.
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    Gemini Robotics 2

    Gemini Robotics 2

    Google DeepMind

    Gemini Robotics 2 is Google DeepMind’s intelligence layer for adaptable robots, bringing whole-body control, advanced dexterity, embodied reasoning, and multi-robot collaboration to physical AI. It includes three models. Gemini Robotics 2 is a vision-language-action model that converts visual and language input into motor control, enabling humanoids and bi-arm robots to act from feet to fingertips. It can coordinate walking, crouching, reaching, balancing, and object manipulation, while controlling five-fingered hands or standard grippers for delicate and precise tasks. Gemini Robotics ER 2 serves as the high-level brain, communicating with people, understanding its surroundings, planning multi-step tasks that last several minutes, coordinating actions with the VLA, tracking progress, self-correcting failures, and allowing different robots to work together.
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    Gemini 2.0 Pro
    Gemini 2.0 Pro is Google DeepMind's most advanced AI model, designed to excel in complex tasks such as coding and intricate problem-solving. Currently in its experimental phase, it features an extensive context window of two million tokens, enabling it to process and analyze vast amounts of information efficiently. A standout feature of Gemini 2.0 Pro is its seamless integration with external tools like Google Search and code execution environments, enhancing its ability to provide accurate and comprehensive responses. This model represents a significant advancement in AI capabilities, offering developers and users a powerful resource for tackling sophisticated challenges.
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    Lyria 3 Pro
    Lyria 3 Pro is an advanced AI music generation model developed by Google DeepMind that enables users to create longer, high-quality music tracks with enhanced structure and control. It allows the generation of tracks up to three minutes long, supporting detailed composition elements such as intros, verses, choruses, and bridges. The model is designed to better understand musical structure, making it easier to produce cohesive and dynamic audio outputs. Lyria 3 Pro is integrated across multiple Google platforms, including Gemini Enterprise Agent Platform, Google AI Studio, and the Gemini app. It supports a wide range of use cases, from content creation and video production to large-scale audio generation for businesses. The model also includes safeguards to prevent imitation of specific artists and ensures responsible AI usage through built-in protections and watermarking. Overall, Lyria 3 Pro enhances creative workflows by providing powerful, customizable music generation capabilities.
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    Nano Banana 2 Lite
    Nano Banana 2 Lite is Google’s fastest Gemini Image model in the Nano Banana family, built for high throughput, speed, and scale. Also known as Gemini 3.1 Flash Lite Image, it is designed for rapid ideation and high-velocity developer pipelines where speed, iteration, and efficient production are the primary constraints. Developers can use it as the recommended replacement for the first version of Nano Banana, gaining immediate benefits across key performance dimensions while continuing to build image-generation and editing workflows through Google AI Studio, the Gemini API, and Gemini Enterprise Agent Platform. Nano Banana 2 Lite is optimized for near-real-time, high-volume workflows where ultra-low latency is critical, delivering text-to-image outputs in just a few seconds and making it well-suited for interactive prototyping, visual drafting, creative exploration, and large-scale image generation.
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    Gemini 3.1 Flash-Lite
    Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building.
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    Gemini Pro
    Gemini Pro is a powerful multimodal AI model developed by Google as part of the broader Gemini family of large language models. It is designed to handle a wide range of tasks, including text generation, reasoning, coding, and data analysis. The model can process multiple types of input such as text, images, audio, and video, making it highly versatile for real-world applications. Gemini Pro is optimized for delivering accurate, context-aware responses across complex workflows. It integrates seamlessly with Google products and cloud services, enabling scalable AI-powered applications. The model is commonly used for tasks like content creation, summarization, and conversational AI. It balances performance and efficiency, making it suitable for both developers and enterprise users. Overall, it serves as a robust foundation for building intelligent AI-driven solutions.