Alternatives to GPT-Realtime-2.1
Compare GPT-Realtime-2.1 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GPT-Realtime-2.1 in 2026. Compare features, ratings, user reviews, pricing, and more from GPT-Realtime-2.1 competitors and alternatives in order to make an informed decision for your business.
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Nemotron 3 Ultra
NVIDIA
Nemotron 3 Nano is a compact, open large language model in NVIDIA’s Nemotron 3 family, designed for efficient agentic reasoning, conversational AI, and coding tasks. It uses a hybrid Mixture-of-Experts Mamba-Transformer architecture that activates only a small subset of parameters per token, enabling low-latency inference while maintaining strong accuracy and reasoning performance. It has approximately 31.6 billion total parameters with around 3.2 billion active (3.6 billion including embeddings), allowing it to achieve higher accuracy than previous Nemotron 2 Nano while using less computation per forward pass. Nemotron 3 Nano supports long-context processing of up to one million tokens, enabling it to handle large documents, multi-step workflows, and extended reasoning chains in a single pass. It is designed for high-throughput, real-time execution, excelling in multi-turn conversations, tool calling, and agent-based workflows where tasks require planning, reasoning, and more. -
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Inkling
Thinking Machines Lab
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.Starting Price: Free -
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MiniMax M3
MiniMax
MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.Starting Price: Free -
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TML-interaction-small
Thinking Machines Lab
TML-Interaction-Small is a real-time multimodal interaction model developed by Thinking Machines Lab to enable more natural and collaborative human-AI communication across audio, video, and text. Unlike traditional turn-based AI systems that rely on external scaffolding and delayed interactions, TML-Interaction-Small is designed around continuous micro-turn exchanges that allow the model to perceive, respond, listen, speak, and react simultaneously in real time. The model uses a time-aware architecture that processes 200ms interaction windows, enabling seamless interruptions, simultaneous speech, visual cue detection, and live collaborative workflows without requiring separate dialog management systems. TML-Interaction-Small supports capabilities such as real-time conversation, proactive interjections, live translation, visual monitoring, tool usage, browsing, and asynchronous reasoning through coordination with a background model. -
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Cartesia Sonic-3
Cartesia
Cartesia Sonic-3 is a real-time, streaming text-to-speech (TTS) model designed to generate ultra-realistic, expressive voice output with extremely low latency, enabling AI systems to speak as fluidly as humans in live interactions. Built on advanced state space model architecture, Sonic delivers high-quality speech while achieving near-instant response times, with audio generation beginning in as little as 40–100 milliseconds, making conversations feel seamless rather than delayed. It is optimized for conversational AI use cases, acting as the “voice layer” for AI agents by converting text into natural-sounding speech that includes emotional nuance such as excitement, empathy, or even laughter. It supports more than 40 languages with native-level voices and accent localization, allowing developers to build globally accessible applications with consistent quality across regions.Starting Price: $4 per month -
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Cartesia Sonic-3.5
Cartesia
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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GPT-Realtime-1.5
OpenAI
GPT-Realtime-1.5 is a flagship voice AI model from OpenAI designed for real-time audio interactions and conversational applications. It supports both audio input and output, making it ideal for voice agents and customer support systems. The model delivers fast performance with high responsiveness, enabling natural, real-time conversations. It can process multiple input types, including text, audio, and images, while generating both text and audio responses. With a 32,000-token context window, it can handle extended conversations and maintain context effectively. The model is optimized for high-performance use cases where speed and accuracy are critical. It also supports function calling, allowing integration with external tools and workflows. Overall, it provides a powerful solution for building interactive, real-time voice applications.Starting Price: $4.00 per 1M tokens (input) -
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Gemini 3.1 Flash Live
Google
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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Grok Voice Think Fast 1.0
SpaceXAI
Grok Voice Think Fast 1.0 is an advanced voice AI model developed by xAI, designed to handle complex, real-world conversational workflows. It excels in multi-step tasks across customer support, sales, and enterprise applications. The model is built for fast, natural conversations while maintaining high accuracy and responsiveness. It supports real-time reasoning without adding latency, allowing it to process and respond intelligently during live interactions. Grok Voice can accurately capture and confirm structured data such as names, addresses, and account details, even in noisy or challenging conditions. It is optimized for global use with support for over 25 languages. The model is capable of handling interruptions, accents, and ambiguous inputs with ease. Overall, it enables businesses to deploy efficient, scalable voice agents for high-volume interactions. -
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Grok Voice Think Fast 2.0
SpaceXAI
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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gpt-realtime
OpenAI
GPT-Realtime is OpenAI’s most advanced, production-ready speech-to-speech model, now accessible through the fully available Realtime API. It delivers remarkably natural, expressive audio with fine-grained control over tone, pace, and accent. The model can comprehend nuanced human audio, including laughter, switch languages mid-sentence, and accurately process alphanumeric details like phone numbers across multiple languages. It significantly improves reasoning and instruction-following (achieving 82.8% on the BigBench Audio benchmark and 30.5% on MultiChallenge) and boasts enhanced function calling, now more reliable, timely, and accurate (scoring 66.5% on ComplexFuncBench). The model supports asynchronous tool invocation so conversations remain fluid even during long-running calls. The Realtime API also offers innovative capabilities such as image input support, SIP phone network integration, remote MCP server connection, and reusable conversation prompts.Starting Price: $20 per month -
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Azure Voice Live API
Microsoft
Azure Voice Live API is a fully managed solution for building low-latency, high-quality speech-to-speech agents through one unified interface. It combines speech recognition, generative AI, and text-to-speech, allowing developers to send audio input and receive audio output, synchronized avatar visuals, and action triggers without manually orchestrating separate backend components or deploying the underlying models. It supports more than 140 speech-to-text locales and over 600 standard voices across 150+ text-to-speech locales, with options for phrase lists, custom speech, custom voices, and brand-aligned avatars. Developers can choose among multiple generative AI models, including GPT-Realtime, GPT-5, GPT-4.1, GPT-4o, Phi, and compatible bring-your-own models, depending on the intelligence, speed, and latency required. Advanced conversational features include noise suppression, echo cancellation, robust interruption detection, and end-of-turn detection. -
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GPT-Realtime-2
OpenAI
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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Mercury 2
Inception
Mercury 2 is the first reasoning model fast enough to pick up the phone, a reasoning diffusion language model built for real-time voice agents. Instead of making callers wait through seconds of dead air while an autoregressive model generates thinking tokens one by one, Mercury 2 uses a diffusion large language model architecture to generate tokens in parallel, decoding 1000+ tokens per second on standard NVIDIA GPUs. That speed is fast enough to run a full reasoning pass and start speaking within the latency budget of a natural conversation, reducing the cost of reasoning from seconds of silence to roughly 300 milliseconds. Mercury models work by corrupting clean text into noise, then training a standard Transformer to reverse the process and predict clean text across all positions simultaneously. Because each denoising pass touches many tokens, generation uses the GPU more efficiently than one-token-at-a-time decoding, making custom-silicon-like speed possible on NVIDIA H100s. -
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GPT‑Realtime‑Whisper
OpenAI
GPT-Realtime-Whisper is OpenAI’s streaming transcription model built for low-latency speech-to-text experiences in live products. It transcribes audio as people speak, helping voice-enabled apps feel faster, more responsive, and more natural, from captions that appear in the moment to meeting notes that keep up with the conversation. It makes live speech usable inside business workflows as it happens, so teams can power captions for meetings, classrooms, broadcasts, and events, generate notes and summaries while conversations are still in progress, build voice agents that need to understand users continuously, and create faster follow-up workflows for high-volume spoken interactions. It is part of a new generation of real-time voice models in the API that can reason, translate, and transcribe as people speak, moving real-time audio beyond simple call-and-response toward voice interfaces that can listen, translate, transcribe, and take action as a conversation unfolds.Starting Price: $0.017 per minute -
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Reka Flash 3
Reka
Reka Flash 3 is a 21-billion-parameter multimodal AI model developed by Reka AI, designed to excel in general chat, coding, instruction following, and function calling. It processes and reasons with text, images, video, and audio inputs, offering a compact, general-purpose solution for various applications. Trained from scratch on diverse datasets, including publicly accessible and synthetic data, Reka Flash 3 underwent instruction tuning on curated, high-quality data to optimize performance. The final training stage involved reinforcement learning using REINFORCE Leave One-Out (RLOO) with both model-based and rule-based rewards, enhancing its reasoning capabilities. With a context length of 32,000 tokens, Reka Flash 3 performs competitively with proprietary models like OpenAI's o1-mini, making it suitable for low-latency or on-device deployments. The model's full precision requires 39GB (fp16), but it can be compressed to as small as 11GB using 4-bit quantization. -
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Command A Reasoning
Cohere AI
Command A Reasoning is Cohere’s most advanced enterprise-ready language model, engineered for high-stakes reasoning tasks and seamless integration into AI agent workflows. The model delivers exceptional reasoning performance, efficiency, and controllability, scaling across multi-GPU setups with support for up to 256,000-token context windows, ideal for handling long documents and multi-step agentic tasks. Organizations can fine-tune output precision and latency through a token budget, allowing a single model to flexibly serve both high-accuracy and high-throughput use cases. It powers Cohere’s North platform with leading benchmark performance and excels in multilingual contexts across 23 languages. Designed with enterprise safety in mind, it balances helpfulness with robust safeguards against harmful outputs. A lightweight deployment option allows running the model securely on a single H100 or A100 GPU, simplifying private, scalable use. -
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Amazon Nova Sonic
Amazon
Amazon Nova Sonic is a state-of-the-art speech-to-speech model that delivers real-time, human-like voice conversations with industry-leading price performance. It unifies speech understanding and generation into a single model, enabling developers to create natural, expressive conversational AI experiences with low latency. Nova Sonic adapts its responses based on the prosody of input speech, such as pace and timbre, resulting in more natural dialogue. It supports function calling and agentic workflows to interact with external services and APIs, including knowledge grounding with enterprise data using Retrieval-Augmented Generation (RAG). It provides robust speech understanding for American and British English across various speaking styles and acoustic conditions, with additional languages coming soon. Nova Sonic handles user interruptions gracefully without dropping conversational context and is robust to background noise. -
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Vision Agents
Stream
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.Starting Price: Free -
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Gemini 2.5 Flash TTS
Google
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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GPT-5 mini
OpenAI
GPT-5 mini is a streamlined, faster, and more affordable variant of OpenAI’s GPT-5, optimized for well-defined tasks and precise prompts. It supports text and image inputs and delivers high-quality text outputs with a 400,000-token context window and up to 128,000 output tokens. This model excels at rapid response times, making it suitable for applications requiring fast, accurate language understanding without the full overhead of GPT-5. Pricing is cost-effective, with input tokens at $0.25 per million and output tokens at $2 per million, providing savings over the flagship model. GPT-5 mini supports advanced features like streaming, function calling, structured outputs, and fine-tuning, but does not support audio input or image generation. It integrates well with various API endpoints including chat completions, responses, and embeddings, making it versatile for many AI-powered tasks.Starting Price: $0.25 per 1M tokens -
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Gemini Live API
Google
The Gemini Live API is a preview feature that enables low-latency, bidirectional voice and video interactions with Gemini. It allows end users to experience natural, human-like voice conversations and provides the ability to interrupt the model's responses using voice commands. The model can process text, audio, and video input, and it can provide text and audio output. New capabilities include two new voices and 30 new languages with configurable output language, configurable image resolutions (66/256 tokens), configurable turn coverage (send all inputs all the time or only when the user is speaking), configurable interruption settings, configurable voice activity detection, new client events for end-of-turn signaling, token counts, a client event for signaling the end of stream, text streaming, configurable session resumption with session data stored on the server for 24 hours, and longer session support with a sliding context window. -
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GPT-5 nano
OpenAI
GPT-5 nano is OpenAI’s fastest and most affordable version of the GPT-5 family, designed for high-speed text processing tasks like summarization and classification. It supports text and image inputs, generating high-quality text outputs with a large 400,000-token context window and up to 128,000 output tokens. GPT-5 nano offers very fast response times, making it ideal for applications requiring quick turnaround without sacrificing quality. Pricing is extremely competitive, with input tokens costing $0.05 per million and output tokens $0.40 per million, making it accessible for budget-conscious projects. The model supports advanced API features such as streaming, function calling, structured outputs, and fine-tuning. While it supports image input, it does not handle audio input or web search, focusing on core text tasks efficiently.Starting Price: $0.05 per 1M tokens -
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Grok Speech to Text (STT)
SpaceXAI
Grok Speech to Text is a standalone audio API built to help developers integrate fast, accurate transcription into any application. Built on the same stack that powers Grok Voice, Tesla vehicles, and Starlink customer support, the API is designed for use cases such as voice agents, real-time transcription tools, accessibility solutions, podcasts, meeting capture, telephony, and interactive audio experiences. Grok STT can generate transcripts from large audio files through a REST API or transcribe speech in real time through a low-latency WebSocket API. It includes word-level timestamps, speaker diarization, multichannel support, and intelligent Inverse Text Normalization that converts spoken language into properly formatted structured output for numbers, dates, currencies, and more. Grok Speech to Text is evaluated across phone calls, meetings, video and podcast content, and telephony, with strong performance in entity recognition and business use cases. -
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Gemini Audio
Google
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.Starting Price: Free -
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GPT-4o mini
OpenAI
A small model with superior textual intelligence and multimodal reasoning. GPT-4o mini enables a broad range of tasks with its low cost and latency, such as applications that chain or parallelize multiple model calls (e.g., calling multiple APIs), pass a large volume of context to the model (e.g., full code base or conversation history), or interact with customers through fast, real-time text responses (e.g., customer support chatbots). Today, GPT-4o mini supports text and vision in the API, with support for text, image, video and audio inputs and outputs coming in the future. The model has a context window of 128K tokens, supports up to 16K output tokens per request, and has knowledge up to October 2023. Thanks to the improved tokenizer shared with GPT-4o, handling non-English text is now even more cost effective. -
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Nemotron 3 Nano Omni
NVIDIA
NVIDIA Nemotron 3 Nano Omni is an open, omni-modal foundation model designed to unify perception and reasoning across text, images, audio, video, and documents within a single efficient architecture. It eliminates the need for separate models for each modality, reducing inference latency, orchestration complexity, and cost while maintaining consistent cross-modal context. It is purpose-built for agentic AI systems, acting as a perception and context sub-agent that gives larger AI agents the ability to “see, hear, and read” in real time across screens, recordings, and structured or unstructured data. It supports advanced multimodal reasoning tasks such as document understanding, speech recognition, long audio-video analysis, and computer-use workflows, enabling agents to interpret dynamic interfaces and complex environments. Built with a hybrid architecture optimized for long context and throughput, it can process large inputs like multi-page documents.Starting Price: Free -
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Inkling-Small
Thinking Machines Lab
Inkling-Small is an efficient model that offers performance comparable to Inkling at a quarter of its size. It is a Mixture-of-Experts transformer with 276 billion total parameters and 12 billion active parameters, trained on NVIDIA GB300 NVL72 systems. It supports native reasoning across text, images, and audio, variable thinking effort, and context windows of up to one million tokens. Users adjust reasoning effort from minimal to extra high to balance performance and compute. Improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning helped Inkling-Small surpass its larger counterpart on reasoning and coding benchmarks. It performs well in coding and tool-use harnesses, exceeds 80% on SWE-bench Verified, and combines strong reasoning with efficient output. Its encoder-free multimodal architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens.Starting Price: $0.30 per million input tokens -
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GPT-5.4
OpenAI
GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations. -
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Mercury Edit 2
Inception
Mercury Edit 2 is part of Inception Labs’ Mercury family of AI models, designed to perform high-speed reasoning, coding, and editing tasks using a fundamentally different architecture from traditional large language models. It builds on Mercury 2, a diffusion-based reasoning model that generates and refines entire outputs in parallel rather than producing text token by token, enabling significantly faster performance and more responsive editing workflows. Instead of acting like a sequential “typewriter,” the system behaves more like an editor, starting with a rough draft and iteratively improving it across multiple tokens at once, which allows for real-time interaction and rapid iteration in tasks such as code editing, content generation, and agent-based workflows. This architecture delivers throughput of up to around 1,000 tokens per second, making it several times faster than conventional models while maintaining competitive reasoning quality across benchmarks.Starting Price: $0.25 per 1M input tokens -
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OpenAI Realtime API
OpenAI
The OpenAI Realtime API is a newly introduced API, announced in 2024, that allows developers to create applications that facilitate real-time, low-latency interactions, such as speech-to-speech conversations. This API is designed for use cases like customer support agents, AI voice assistants, and language learning apps. Unlike previous implementations that required multiple models for speech recognition and text-to-speech conversion, the Realtime API handles these processes seamlessly in one call, enabling applications to handle voice interactions much faster and with more natural flow. -
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GPT-5.4 Pro
OpenAI
GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently. -
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Sarvam 105B
Sarvam
Sarvam-105B is the flagship large language model in Sarvam’s open source model family, designed to deliver high-performance reasoning, multilingual understanding, and agent-based execution within a single scalable system. Built as a Mixture-of-Experts (MoE) model with approximately 105 billion total parameters, of which only a fraction are activated per token, it achieves strong computational efficiency while maintaining high capability across complex tasks. The model is optimized for advanced reasoning, coding, mathematics, and agentic workflows, making it suitable for tasks that require multi-step problem solving and structured outputs rather than simple conversational responses. Sarvam-105B supports long-context processing of up to around 128K tokens, enabling it to handle large documents, extended conversations, and deep analytical queries without losing coherence.Starting Price: Free -
34
MiMo-V2.5
Xiaomi Technology
Xiaomi MiMo-V2.5 is an advanced open-source AI model designed to combine strong agentic capabilities with native multimodal understanding. It can process and reason across text, images, and audio within a single unified system. The model uses a sparse Mixture-of-Experts architecture with hundreds of billions of parameters for efficient performance. It supports an extended context window of up to one million tokens, enabling long and complex workflows. MiMo-V2.5 is built to handle tasks such as coding, reasoning, and multimodal analysis with high accuracy. It incorporates dedicated visual and audio encoders to enhance perception and cross-modal reasoning. The model demonstrates strong benchmark performance across coding, reasoning, and multimodal tasks. By combining multimodality, efficiency, and agentic intelligence, MiMo-V2.5 advances the capabilities of open-source AI systems. -
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MiniMax Speech 2.8
MiniMax
MiniMax Speech 2.8 is a next-generation AI speech model built to make synthetic voice feel alive, expressive, and deeply human. It focuses on performance in real-world voice agent scenarios, combining ultra-fast response, richer emotional expression, cleaner audio, and stronger cross-lingual performance for products that need natural spoken interaction. Speech 2.8 is designed to reduce the distance between AI voice and real human communication, giving developers and creators more control over how a voice sounds, reacts, and carries meaning. It supports flexible emotion control, allowing users to shape delivery with moods, tone, and expressive direction instead of relying on flat or robotic speech. It can produce speech with more natural pauses, cadence, emphasis, and emotional texture, helping AI characters, assistants, narrators, and interactive agents sound more believable across longer conversations. -
36
Gemini 3 Flash
Google
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. -
37
Gemini 2.5 Pro TTS
Google
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. -
38
Cartesia Ink-Whisper
Cartesia
Cartesia Ink is a family of real-time streaming speech-to-text (STT) models designed to power fast, natural conversations in voice AI applications, acting as the “voice input” layer that converts spoken language into accurate text instantly. Its flagship model, Ink-Whisper, is specifically engineered for conversational environments, delivering ultra-low latency transcription with a time-to-complete-transcript as fast as 66 milliseconds, enabling fluid, human-like interactions without noticeable delays. Unlike traditional transcription systems built for batch processing, Ink is optimized for live dialogue, handling fragmented, variable-length audio through dynamic chunking, which reduces errors and improves responsiveness during pauses, interruptions, or rapid exchanges.Starting Price: $4 per month -
39
OpenAI Whisper
OpenAI
Whisper is an automatic speech recognition (ASR) system developed by OpenAI for converting spoken language into text. It is trained on 680,000 hours of multilingual and multitask audio data collected from the web. The model is designed to handle diverse accents, background noise, and technical language with high accuracy. Whisper supports transcription in multiple languages as well as translation into English. It uses an encoder-decoder Transformer architecture to process audio inputs and generate text outputs. The system can also perform tasks like language identification and timestamp generation. Overall, Whisper enables developers to build robust voice-enabled applications with ease. -
40
GLM-4.7-Flash
Z.ai
GLM-4.7 Flash is a lightweight variant of GLM-4.7, Z.ai’s flagship large language model designed for advanced coding, reasoning, and multi-step task execution with strong agentic performance and a very large context window. It is an MoE-based model optimized for efficient inference that balances performance and resource use, enabling deployment on local machines with moderate memory requirements while maintaining deep reasoning, coding, and agentic task abilities. GLM-4.7 itself advances over earlier generations with enhanced programming capabilities, stable multi-step reasoning, context preservation across turns, and improved tool-calling workflows, and supports very long context lengths (up to ~200 K tokens) for complex tasks that span large inputs or outputs. The Flash variant retains many of these strengths in a smaller footprint, offering competitive benchmark performance in coding and reasoning tasks for models in its size class.Starting Price: Free -
41
gpt-4o-mini Realtime
OpenAI
The gpt-4o-mini-realtime-preview model is a compact, lower-cost, realtime variant of GPT-4o designed to power speech and text interactions with low latency. It supports both text and audio inputs and outputs, enabling “speech in, speech out” conversational experiences via a persistent WebSocket or WebRTC connection. Unlike larger GPT-4o models, it currently does not support image or structured output modalities, focusing strictly on real-time voice/text use cases. Developers can open a real-time session via the /realtime/sessions endpoint to obtain an ephemeral key, then stream user audio (or text) and receive responses in real time over the same connection. The model is part of the early preview family (version 2024-12-17), intended primarily for testing and feedback rather than full production loads. Usage is subject to rate limits and may evolve during the preview period. Because it is multimodal in audio/text only, it enables use cases such as conversational voice agents.Starting Price: $0.60 per input -
42
Amazon Nova 2 Sonic
Amazon
Nova 2 Sonic is Amazon’s real-time speech-to-speech model designed to deliver natural, flowing voice interactions without relying on separate systems for text and audio. It combines speech recognition, speech generation, and text processing in a single model, enabling smooth, human-like conversations that can shift effortlessly between voice and text. With expanded multilingual support and expressive voice options, it produces responses that sound more lifelike and contextually aware. Its one-million-token context window allows for long, continuous interactions without losing track of prior details. It supports asynchronous task handling, meaning users can continue speaking, change topics, or ask follow-up questions while background tasks, such as searching for information or completing a request, continue uninterrupted. This makes voice experiences feel more fluid and less bound by traditional turn-based dialog constraints. -
43
Gemini 3.1 Flash TTS
Google
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. -
44
Kimi K2 Thinking
Moonshot AI
Kimi K2 Thinking is an advanced open source reasoning model developed by Moonshot AI, designed specifically for long-horizon, multi-step workflows where the system interleaves chain-of-thought processes with tool invocation across hundreds of sequential tasks. The model uses a mixture-of-experts architecture with a total of 1 trillion parameters, yet only about 32 billion parameters are activated per inference pass, optimizing efficiency while maintaining vast capacity. It supports a context window of up to 256,000 tokens, enabling the handling of extremely long inputs and reasoning chains without losing coherence. Native INT4 quantization is built in, which reduces inference latency and memory usage without performance degradation. Kimi K2 Thinking is explicitly built for agentic workflows; it can autonomously call external tools, manage sequential logic steps (up to and typically between 200-300 tool calls in a single chain), and maintain consistent reasoning.Starting Price: Free -
45
Grok Build 0.1
SpaceXAI
Grok Build 0.1 is a specialized AI coding model from xAI designed for agentic software engineering workflows and multi-step development tasks. The model is optimized to help coding agents perform actions such as planning, debugging, implementing changes, and iterating on code rather than simply generating one-time code responses. It supports both text and image inputs while producing text-based outputs, making it useful for analyzing code, screenshots, and technical documentation. Grok Build 0.1 includes support for tool use, structured outputs, function calling, and large-context reasoning capabilities. With a context window of up to 256,000 tokens, the model can process large codebases and complex projects within a single workflow. The platform is built for developers and engineering teams seeking faster and more capable AI-assisted software development.Starting Price: $1 per 1M tokens (input) -
46
Babelbeez
Babelbeez
Babelbeez is a browser-native voice AI designed to function as an automation trigger. It allows website visitors to speak naturally with an AI agent via WebRTC, while simultaneously extracting structured data from the conversation to power your backend workflows. Powered by the OpenAI Realtime API, Babelbeez enables low-latency, interruptible speech-to-speech interactions directly in the browser, eliminating the need for phone numbers or SIP infrastructure. Beyond answering customer queries using your automatically generated knowledge base (RAG), the Babelbeez Entity Extraction Engine identifies key data points—such as intents, contact details, or scheduling preferences—and pushes them as clean JSON payloads to your stack via secure HMAC-signed webhooks.Starting Price: $39/month -
47
Step 3.5 Flash
StepFun
Step 3.5 Flash is an advanced open source foundation language model engineered for frontier reasoning and agentic capabilities with exceptional efficiency, built on a sparse Mixture of Experts (MoE) architecture that selectively activates only about 11 billion of its ~196 billion parameters per token to deliver high-density intelligence and real-time responsiveness. Its 3-way Multi-Token Prediction (MTP-3) enables generation throughput in the hundreds of tokens per second for complex multi-step reasoning chains and task execution, and it supports efficient long contexts with a hybrid sliding window attention approach that reduces computational overhead across large datasets or codebases. It demonstrates robust performance on benchmarks for reasoning, coding, and agentic tasks, rivaling or exceeding many larger proprietary models, and includes a scalable reinforcement learning framework for consistent self-improvement.Starting Price: Free -
48
Oxlo.ai
Oxlo.ai
Oxlo.ai is a privacy-first inference stack for agents, built to run frontier-class open-source models with unlimited agentic tool calls, secure failover, and zero data retention or training. It gives developers request-based access to curated open models through a unified HTTP API designed for predictable usage, low-latency inference, and clean integration into production systems. Teams can call models through OpenAI-compatible endpoints, switch from another provider by changing the base URL and API key, and keep support for streaming, function calling, JSON mode, vision models, embeddings, and image generation. Oxlo.ai supports more than 40 models across text, chat, reasoning, coding, image generation, audio, embeddings, computer vision, vision-language, speech-to-text, text-to-speech, long-context, and detection workflows.Starting Price: $80 per month -
49
Gemini 3.5 Flash-Lite
Google
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 -
50
Gemini 3.5 Live Translate
Google
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.
