Alternatives to Gemini 3.8 Flash

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

  • 1
    Claude Fable 5.1
    Claude Fable 5.1 is Anthropic’s advanced AI model for coding, knowledge work, research, and long-running agentic tasks. It is designed to improve on Claude Fable 5 with stronger performance across software engineering, scientific research, multidisciplinary reasoning, computer use, business workflows, and complex problem solving. The model can handle extended multi-step work, verify its own results, diagnose difficult software issues, and operate effectively across tool-heavy workflows. Anthropic also reduced cache-read pricing for Fable 5.1, lowering typical usage costs compared with Fable 5 and creating larger savings for highly agentic workloads. Fable 5.1 includes updated safeguards intended to reduce false positives while allowing more legitimate cybersecurity tasks such as vulnerability discovery for defensive purposes. The model is available through Claude products, the Claude API, Amazon Web Services, Google Cloud, and Microsoft Azure.
    Starting Price: $10 per 1M tokens (input)
  • 2
    GPT-5.6 Sol
    GPT-5.6 Sol is a next-generation OpenAI model designed for advanced reasoning, coding, agentic workflows, biology analysis, cybersecurity support, and complex knowledge work. It is part of the GPT-5.6 model family alongside Terra and Luna, with Sol positioned as the flagship model for the most demanding tasks. The model introduces a new max reasoning effort for deeper thinking and an ultra mode that uses subagents to accelerate complex work beyond a single-agent approach. GPT-5.6 Sol shows strong performance in command-line coding workflows, long-horizon security tasks, genomics analysis, vulnerability research, debugging, patch development, and defensive testing. OpenAI pairs the model’s stronger capabilities with layered safeguards, real-time misuse classifiers, account-level review, automated red-teaming, and enterprise controls for sensitive workflows. GPT-5.6 Sol helps developers, enterprises, researchers, and security teams complete sophisticated technical work.
    Starting Price: $4 per 1M tokens (input)
  • 3
    Claude Mythos 5.1
    Claude Mythos 5.1 is Anthropic’s newest Mythos-class model, designed for advanced cybersecurity, biology, scientific research, coding, and long-running knowledge work. It is the same underlying model as Claude Fable 5.1 but uses different safeguards: Fable 5.1 is generally available, while Mythos 5.1 is restricted to trusted access programs with safeguards specifically designed for cybersecurity and life sciences research. The model sets a new performance frontier for agentic coding and demonstrates the strongest cyber capabilities of any Anthropic model released to date. In scientific research, Mythos 5.1 can work with specialized tools and complex workflows across molecular design, computational biology, and other technical domains. In Anthropic’s experiments, it designed high-affinity protein binders across multiple targets and achieved its strongest measured hit rate to date. It also optimized seven open-source protein and genomics deep learning models.
  • 4
    Grok 4.6

    Grok 4.6

    SpaceXAI

    Grok 4.6 is an xAI model designed for long-running agents, ambitious interactive projects, visual work, coding, research, and knowledge workflows. The model builds on Grok 4.5 with stronger support for multi-step tasks that require sustained reasoning across codebases, information analysis, application development, and work artifact creation. Grok 4.6 can help turn broad product ideas into working first versions by researching domains, structuring applications, implementing core interactions, and refining results through feedback. It is trained across agentic tasks such as knowledge work, general coding, kernel optimization, web development, computer-aided design, and other technical environments. The model is available in Cursor, Grok Build, the xAI API, and partners such as OpenRouter, Vercel, and Cloudflare. Built for developers, builders, and teams working on complex projects, Grok 4.6 helps accelerate coding, agentic workflows, visual applications, and technical execution.
    Starting Price: $2 per 1M tokens (input)
  • 5
    Claude Opus 5

    Claude Opus 5

    Anthropic

    Claude Opus 5 is Anthropic’s advanced everyday AI model built for coding, knowledge work, problem-solving, visual outputs, and production AI workflows. The model delivers stronger performance than Opus 4.8 at the same base price and is positioned as a cost-effective alternative close to Claude Fable 5 frontier intelligence. Claude Opus 5 supports configurable effort settings so users can optimize for intelligence, speed, or token efficiency. It performs especially well on software engineering, automation, computer use, scientific research, and knowledge work evaluations. The model is available on Claude Max, Claude Pro, Claude API, Claude Code, and other Claude platforms, with Fast mode available at a higher price. Built for developers, researchers, enterprises, and everyday Claude users, Claude Opus 5 helps teams complete complex tasks with stronger verification, careful iteration, and practical cost efficiency.
    Starting Price: $5 per 1M tokens (input)
  • 6
    Claude Fable 5
    Claude Fable 5 is an advanced AI model from Anthropic designed to assist with software engineering, research, knowledge work, vision tasks, and complex reasoning. Built on the Mythos-class architecture, it delivers significantly improved performance across coding, analysis, and long-context workflows. The model can handle extended autonomous tasks while maintaining focus and consistency over large amounts of information. Claude Fable 5 integrates advanced reasoning, multimodal understanding, and memory capabilities to support professional and enterprise use cases. Anthropic has implemented specialized safeguards that automatically route certain high-risk cybersecurity, biology, chemistry, and model distillation requests to a different model. Claude Fable 5 helps organizations and professionals accelerate complex work while maintaining strong safety and governance controls.
    Starting Price: $10 per 1 million (input)
  • 7
    Claude Mythos 5
    Claude Mythos 5 is Anthropic’s most advanced restricted-access AI model, designed for trusted cyberdefenders, infrastructure providers, and select research organizations. It uses the same underlying model as Claude Fable 5 but provides lifted safeguards in approved areas for specialized high-trust use cases. The model delivers exceptional capabilities in cybersecurity, software engineering, scientific research, long-context reasoning, vision, and autonomous task execution. Anthropic initially deployed Claude Mythos 5 through Project Glasswing in collaboration with the U.S. government to help protect critical software and infrastructure. The model also shows strong potential in life sciences, including protein design, molecular biology hypothesis generation, and genomics research. Claude Mythos 5 is built for organizations that need frontier AI capabilities under controlled, trusted-access conditions.
    Starting Price: $10 per 1 million (input)
  • 8
    Claude Sonnet 5
    Claude Sonnet 5 is Anthropic's latest AI model, designed to deliver stronger agentic capabilities for coding, reasoning, tool use, and knowledge work while maintaining the efficiency of the Sonnet family. The model can independently plan tasks, use external tools such as browsers and terminals, and complete complex workflows that previously required larger AI models. Sonnet 5 significantly improves upon Claude Sonnet 4.6 with better reasoning, coding performance, reduced hallucinations, stronger safety behavior, and more effective autonomous task execution. It is available across Claude plans and through the Claude API with OpenAI-style developer access for application integration. Anthropic also introduced lower introductory API pricing, making Sonnet 5 a cost-effective option for developers building AI-powered products. By combining advanced agentic capabilities with improved safety and competitive pricing, Claude Sonnet 5 helps developers build more capable AI applications.
    Starting Price: $2 per 1M tokens (input)
  • 9
    GLM-5.2
    GLM-5.2 is an advanced AI foundation model designed to support complex reasoning, coding, and long-range agentic tasks. It helps developers, teams, and organizations build intelligent systems that can understand instructions, solve technical problems, and assist with demanding workflows. The model is especially useful for software engineering, automation, research, and productivity-focused applications. GLM-5.2 is built to handle large amounts of context, making it suitable for projects that require deeper understanding across extended conversations, documents, or codebases. Its mixture-of-experts design helps balance strong performance with more efficient model operation. GLM-5.2 gives businesses and developers a powerful AI tool for creating smarter applications, improving technical workflows, and supporting advanced digital experiences.
  • 10
    GLM-5.3
    GLM-5.3 is Z.ai’s frontier coding model designed for complex software engineering, long-horizon agent tasks, and advanced post-training research. The model uses the same base model as GLM-5.2, with improvements coming from scaled post-training across more environments, more diverse tasks, and larger compute investment. GLM-5.3 delivers stronger coding performance, better task ownership, improved benchmark results, and greater efficiency across realistic development workflows. It is built to handle complex coding tasks, production-style engineering work, research environments, automation tasks, and agentic workflows that require multi-step execution. The model also shows emergent cyber capabilities in vulnerability discovery and exploitation-chain reasoning, with safety evaluation and hardening planned before open-weight release.
  • 11
    GPT-5.6 Luna
    GPT-5.6 Luna is the fast and affordable model in OpenAI’s GPT-5.6 series, built to bring strong capability to users and developers who need practical intelligence with lower overhead. In the new GPT-5.6 naming system, the number identifies the model generation, while Sol, Terra, and Luna identify durable capability tiers that can advance on their own cadence, giving people and developers clearer choices across intelligence, speed, and cost. Luna sits alongside Sol, the flagship model, and Terra, the balanced model for everyday work, as part of a family designed for broader access to next-generation AI. During the limited preview, GPT-5.6 models are initially available through the API and Codex to a select group of trusted partners and organizations, with plans for broader availability in ChatGPT, Codex, and the API. OpenAI developed GPT-5.6 Sol, Terra, and Luna with its most robust safeguards to date, with configurations matched to each model’s capabilities.
    Starting Price: $0.20 per 1M tokens (input)
  • 12
    GPT-5.6 Terra
    GPT-5.6 Terra is a balanced model in the GPT-5.6 series designed for everyday work, coding, agentic workflows, cybersecurity support, biology analysis, and enterprise automation. It sits between GPT-5.6 Sol, the flagship model, and GPT-5.6 Luna, the faster and lower-cost option. Terra is positioned to deliver competitive performance to GPT-5.5 while being significantly cheaper to run. The model supports improved reasoning, coding, tool coordination, long-horizon workflows, and legitimate defensive security work. It is part of a model family built with layered safeguards, including trained refusals, real-time misuse classifiers, account-level review, differentiated access, monitoring, and continued red-team testing. GPT-5.6 Terra helps developers, enterprises, and technical teams access strong AI capabilities with a more practical balance of intelligence, speed, and cost.
    Starting Price: $2 per 1M tokens (input)
  • 13
    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.
  • 14
    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)
  • 15
    Kimi K3

    Kimi K3

    Moonshot AI

    Kimi K3 is Moonshot AI’s most capable model, built for frontier intelligence scenarios such as software engineering, knowledge work, deep reasoning, and multimodal understanding. The model has 2.8 trillion parameters and uses Kimi Delta Attention, a hybrid linear attention mechanism, along with Attention Residuals for long-context performance. Kimi K3 supports a 1 million token context window, making it useful for analyzing large codebases, long documents, complex knowledge bases, and multi-step workflows. It includes native visual understanding for images and videos, with support for structured message formats, base64 image input, uploaded video files, and multimodal reasoning. Developers can use Kimi K3 through an OpenAI-compatible API with support for streaming, structured JSON output, partial mode, custom tools, dynamic tool loading, and automatic context caching.
    Starting Price: $3 per 1M tokens (input)
  • 16
    Grok 4.5

    Grok 4.5

    SpaceXAI

    Grok 4.5 is SpaceXAI’s advanced AI model built for coding, agentic tasks, engineering work, and knowledge-intensive productivity. The model is trained on coding, science, engineering, and math data, with reinforcement learning focused on multi-step software engineering and technical workflows. It is designed to handle real-world development tasks such as debugging, Rust and C/C++ work, terminal tasks, long-running agentic rollouts, and end-to-end app creation from a single prompt. Grok 4.5 is also built for fast serving, token efficiency, and lower-cost execution, with pricing based on input and output token usage. Beyond coding, the model supports business productivity tasks in Grok Build, including Excel modeling, PowerPoint diagram creation, Word writing, and research-assisted office workflows. Available through Grok Build, Cursor, and the SpaceXAI API console, Grok 4.5 gives developers and teams a high-performance model for building software, automating work, and more.
    Starting Price: $2 per million input tokens
  • 17
    Qwen3.8-Max
    Qwen3.8-Max is Qwen’s most capable model to date, built as a Max-class AI model for coding, work, research, long-horizon tasks, and multimodal agents. It scales to 2.4 trillion parameters with 95 billion active parameters and is available through QwenCloud. The model is designed to complete complex, open-ended tasks end to end with greater reliability and minimal human involvement. Qwen3.8-Max supports autonomous coding workflows, agentic development, research reproduction, visual reasoning, document understanding, video analysis, and real-world productivity tasks. It can integrate with popular agent frameworks and coding assistants, including Claude Code, Codex, Qoder CLI, Qwen Code, and OpenClaw. Built for developers, researchers, enterprises, and AI agent builders, Qwen3.8-Max helps teams automate sophisticated work across code, documents, tools, interfaces, and multimodal content.
    Starting Price: $2 per 1M (input)
  • 18
    Gemini 3.7 Flash
    Gemini 3.7 Flash is Google’s most intelligent workhorse model yet for coding and agents, delivering substantial improvements across software engineering, knowledge work, web development, and complex business workflows. It shows stronger performance in debugging and issue resolution, higher first-pass code accuracy, and improved generation of production-ready code. For web development, the model creates more functional layouts and feature-complete applications in fewer prompts, with strong design adherence when working from screenshots, images, or complete design systems. In knowledge-dense fields such as finance, law, and biosciences, it provides improved reasoning, accuracy, and complex-document understanding. Gemini 3.7 Flash also performs more effectively on real-world workflow automation and multimodal tasks, supporting use cases ranging from interactive web experiences and data stories to robotics and dynamically generated 3D content.
    Starting Price: $0.75 per 1M tokens (input)
  • 19
    Claude Opus 4.8
    Claude Opus 4.8 is a powerful AI model from Anthropic designed to deliver stronger coding, reasoning, agentic workflows, and advanced collaboration capabilities for developers, enterprises, and AI-powered productivity tasks. The model builds on Claude Opus 4.7 with improvements across coding benchmarks, practical knowledge work, alignment, and reliability while maintaining the same pricing structure. Claude Opus 4.8 introduces enhanced honesty and reasoning behavior, making it less likely to generate unsupported claims or overlook flaws during complex tasks such as software development and agent execution. The release also includes new features such as effort control settings, fast mode for lower-cost high-speed processing, and dynamic workflows in Claude Code that allow the system to coordinate hundreds of parallel subagents for large-scale tasks.
    Starting Price: $5 per 1M (input)
  • 20
    DeepSeek-V4-Pro
    DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.
    Starting Price: $0.435 per 1M tokens (input)
  • 21
    Composer 2.5
    Composer 2.5 is the latest AI coding model released by Cursor, offering major improvements in intelligence, collaboration, and long-task performance compared to Composer 2. The model is designed to follow complex instructions more accurately while providing a smoother and more natural user experience during coding sessions. Cursor enhanced Composer 2.5 through larger-scale training, more advanced reinforcement learning environments, and improved behavioral tuning focused on communication and effort calibration. The model uses targeted reinforcement learning with textual feedback to correct specific mistakes during training, helping it avoid issues like invalid tool calls or poor coding behavior. Composer 2.5 was also trained using significantly more synthetic coding tasks, enabling it to handle increasingly difficult programming challenges and real-world development scenarios.
  • 22
    GLM-5.3-Flash
    GLM-5.3-Flash is Z.ai’s natively multimodal model in the GLM-5 series (previously previewed as Ox Alpha), designed to deliver strong coding, agentic, visual, and knowledge-work performance at relatively low inference cost. It uses 320 billion total parameters with 18 billion active parameters, along with a hybrid architecture that combines sparse and linear attention to reduce the cost of long-context processing. The model supports context lengths of up to one million tokens and was trained on a 30-trillion-token multimodal corpus. GLM-5.3-Flash can reason across text, images, documents, interfaces, dashboards, and other visual information while using that feedback to refine its own outputs. Z.ai reports substantial gains over GLM-5.2 on coding and agentic benchmarks, including DeepSWE and AutomationBench, while approaching higher-cost frontier models on several evaluations.
    Starting Price: $0.15 per 1M tokens (input)
  • 23
    Muse Spark 1.1
    Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.
    Starting Price: $1.25 per 1M tokens (input)
  • 24
    Muse Spark 1.2
    Muse Spark 1.2 is Meta’s coding-focused model update designed to power Muse Code and improve software engineering workflows. The model is built for code generation, complex debugging, codebase understanding, long-horizon development tasks, and end-to-end developer workflows. Muse Spark 1.2 was co-trained with Muse Code to improve performance inside the terminal coding agent environment. It supports planning, goal conditioning, context compaction, subagent coordination, and iterative coding workflows across large repositories. The model was trained with expanded coding compute, diverse development environments, self-improvement loops, and long-running engineering tasks. Built for AI developers and software teams, Muse Spark 1.2 helps agents plan, write, validate, debug, and optimize code with greater autonomy.
    Starting Price: $1.25 per 1M tokens (input)
  • 25
    MiniMax M3

    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: $0.30 per million input tokens
  • 26
    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)
  • 27
    Gemini 3.5 Flash Cyber
    Gemini 3.5 Flash Cyber is a specialized cyber-focused model built on Gemini 3.5 Flash and fine-tuned to find, validate, and fix cybersecurity vulnerabilities efficiently at scale. It is designed for defensive security workflows where organizations need to identify critical weaknesses faster and generate reliable patches before those issues can be exploited. Flash’s combination of performance and efficiency makes it a strong foundation for scanning code, reasoning about security flaws, validating whether findings are real, and proposing targeted remediations across large software environments. Within CodeMender, multiple Gemini 3.5 Flash Cyber agents work together and combine their findings into a single report, helping the system investigate vulnerabilities from different angles and improve the quality of the final result. This coordinated agent setup delivers competitive frontier performance on CyberGym, a benchmark for evaluating cybersecurity capabilities.
  • 28
    Seed2.1 Pro

    Seed2.1 Pro

    ByteDance

    Seed2.1 Pro is a next-generation AI productivity model built to handle complex, real-world work across general agents, code engineering, and multimodal understanding. It reliably executes multi-step tasks for high-value office work and everyday consultation, including project planning, file processing, research, tool use, spreadsheet analysis, lesson-plan slide generation, and industry report creation across tools and environments. In software development workflows, Seed2.1 Pro strengthens end-to-end delivery by improving requirement understanding, architecture design, coding, debugging, implementation, and validation. Its agent capabilities are designed to make steady progress on difficult tasks and return practical, verifiable results rather than isolated responses. The model also advances knowledge, reasoning, visual understanding, spatial reasoning, and long-context processing, giving agents a stronger foundation for complex decision-making and execution.
  • 29
    GPT-5.5

    GPT-5.5

    OpenAI

    GPT-5.5 is an advanced AI model designed to handle complex, real-world tasks with greater autonomy and efficiency. It quickly understands user intent and can execute multi-step workflows such as coding, research, data analysis, and document creation with minimal guidance. Instead of requiring step-by-step instructions, GPT-5.5 plans tasks, uses tools, evaluates outputs, and continues working until completion. It excels in knowledge work, software development, and analytical problem-solving, helping users move from idea to execution faster. The model is built to operate across tools and environments, making it highly effective for modern digital workflows. With strong reasoning and persistence, GPT-5.5 enables individuals and teams to complete demanding work more efficiently and accurately.
    Starting Price: $5 per 1M tokens (input)
  • 30
    Inkling

    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.
  • 31
    EchoInk

    EchoInk

    Echo360

    EchoInk is an interactive content authoring and publishing solution from Echo360 that helps organizations create, curate, update, and distribute mobile-ready learning content. The platform supports course content, modules, digital learning materials, templates, interactive widgets, video, and responsive design previews for laptops, tablets, and phones. Teams can collaborate in real time, use standard or bespoke templates, track comments and edits, and publish content across an organization or external partner network. EchoInk integrates with LMS and LXP platforms, allowing dynamic digital content to be delivered inside existing learning environments. User data can also be exported to business intelligence tools and learning record stores for deeper insights into learner behavior and performance.
  • 32
    Fugu-Ultra v1.1
    Fugu-Ultra v1.1 is Sakana AI’s upgraded multi-agent orchestration model for complex coding, agentic work, and advanced reasoning. Rather than relying on one model, it dynamically coordinates a diverse pool of frontier models, selecting and combining specialized agents for each task while presenting the system through a single model interface. The v1.1 orchestration upgrade incorporates newer frontier models and improves performance across every tracked benchmark, with gains of up to 7.9 points over v1.0 and particularly strong results on ProgramBench and Terminal Bench 2.1. Fugu can now be used directly inside Claude Code through Claude Code-compatible endpoints, bringing a coordinated team of models into familiar terminal workflows for writing, debugging, reviewing, and executing code. A one-command installer configures the integration on Ubuntu and macOS, while manual setup is available for Windows and other environments.
    Starting Price: $6 per 1M tokens (input)
  • 33
    Muse Glimmer
    Muse Glimmer is a 30-billion-parameter open-weights model from Meta Superintelligence Labs, optimized for always-on local agent workflows. Small enough to run on a Mac or PC with a single consumer GPU, it is designed for local agents, function calling, coding, and LLM-as-a-judge evaluation without depending on cloud infrastructure or network access. The model combines long-horizon execution, precise tool calling, multimodal understanding, long-context memory, and instruction following. It can complete end-to-end agentic tasks, sustain multi-step reasoning across extended workflows, recover from failed or unexpected tool calls, and accept interleaved text and images through a dedicated perception encoder for interpreting screenshots, charts, and documents. Muse Glimmer works with OpenClaw and other agentic orchestration patterns, supports controllable reasoning effort, and is trained on data from more than 100 languages.
  • 34
    Muse Spark 1.3
    Muse Spark 1.3 is an AI model with improved performance across agentic and coding tasks, designed to be smarter and more practical for real-world work. It sustains longer-horizon tasks by collaborating with users and managing multiple workflows in a single, long thread. Given an open-ended objective, it uses tools to build context across messy or conflicting sources, correct gaps in its plan, track what it has learned, and produce a final deliverable. It asks clarifying questions when prompts are ambiguous, requests help when stuck, and confirms before taking consequential actions. The model follows complex, long-form instructions more reliably, preserving detailed requirements across multi-step tasks without dropping constraints or drifting from the requested workflow. Improved multitasking allows it to map incoming prompts to the correct task even when users interrupt or redirect previous requests.
    Starting Price: $1.25 per 1M tokens (input)
  • 35
    GPT-5.6 Sol Ultrafast
    GPT-5.6 Sol Ultrafast is a new OpenAI API service tier that runs GPT-5.6 Sol up to 14× faster than Standard processing, bringing frontier intelligence to products and workflows where every second matters. Powered by Cerebras, it can generate up to 750 output tokens per second, allowing advanced reasoning to operate at real-time speeds without requiring a smaller or more specialized model. It is designed for time-sensitive business workflows where faster responses can change what AI can realistically do. Applications include incident response, where models can analyze logs, code changes, traces, and engineer reports while an outage is unfolding; financial research and security, where changing market signals and suspicious transactions can be assessed quickly; and customer support and voice, where complex issues can be resolved without interrupting a live conversation. In commerce, it can answer product questions, check inventory, and personalize recommendations.
  • 36
    GPT-6

    GPT-6

    OpenAI

    GPT-6 is an upcoming OpenAI model expected to represent the next major generation of the GPT model family. While OpenAI has not yet published an official GPT-6 launch page, model card, API ID, pricing, benchmark report, or availability timeline, GPT-6 is likely to build on the direction of the current GPT-5.6 family. As an upcoming model, GPT-6 would be expected to advance reasoning, coding, multimodal understanding, agentic workflows, computer use, and professional knowledge work. It may also extend OpenAI’s work on safer deployment, stronger evaluation, and more capable enterprise and developer tools. Teams should treat GPT-6 as a future model rather than a currently available product until OpenAI releases official documentation. Built for developers, enterprises, researchers, and AI power users, GPT-6 is expected to support the next wave of advanced AI applications once publicly released.
  • 37
    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
  • 38
    Gemma 4

    Gemma 4

    Google

    Gemma 4 is an AI model introduced by Google and built on the Gemini architecture to deliver improved performance and flexibility. The model is designed to run efficiently on a single GPU or TPU, making it more accessible to developers and researchers. Gemma 4 enhances capabilities in natural language understanding and text generation, supporting a wide range of AI-driven applications. Its architecture allows it to handle complex tasks while maintaining efficient resource usage. Developers can use the model to build applications that rely on advanced language processing and automation. The design emphasizes scalability so that it can support both smaller projects and larger AI systems. By combining efficiency with powerful language capabilities, Gemma 4 helps advance the development of modern AI solutions.
  • 39
    Inkling-Small

    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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    MAI-Code-1.1-Flash
    MAI-Code-1.1-Flash is a small, efficient coding model designed to help engineering teams write better code faster. Now in production in GitHub Copilot and built into VS Code, it focuses on real-world developer workflows, with particular improvements for command-line tasks and .NET development based on developer feedback. Compared with the version introduced at Microsoft Build in June, the model produces higher-quality code while using fewer tokens and streaming responses faster. Microsoft reports a 22% improvement on Terminal-Bench 2.1 in GitHub Copilot CLI and a 15% improvement on .NET tasks. Production results also showed a 4% increase in code survival and a 9% increase in return visits. In GitHub Copilot, tokens stream 25% faster and the model uses 25% fewer tokens to complete a task, aiming to deliver faster answers, less waiting, and more useful work from every token. Its gains come from improved training and serving efficiency, with optimization centered on real-world use.
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    Hy4

    Hy4

    Tencent

    Hy4 preview is a new-generation open source Mixture-of-Experts flagship model built for real-world productivity tasks across software engineering, office work, game development, and scientific research. The model contains 770B total parameters with 49B activated per token and supports a 1M-token context window, giving it the capacity to work through large codebases, extensive document collections, and long multi-step tasks. Its 78-layer architecture combines Gated DeepSeek Sparse Attention with IndexCache for cross-layer sparse index reuse and identity Hyper-Connections to expand information flow between layers. A native Multi-Token Prediction layer is included for speculative decoding. Hy4 preview is designed to understand, plan, debug, and verify long-horizon engineering tasks, with additional gains in front-end visual quality and interaction design.
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    Grok 4.7

    Grok 4.7

    SpaceXAI

    Grok 4.7 is an upcoming xAI model expected to continue the Grok 4.x family’s focus on coding, reasoning, agentic workflows, and knowledge work. While xAI has not yet published an official Grok 4.7 launch page, model card, API slug, pricing, or benchmark report, the model is positioned as a future step beyond currently documented Grok 4-era releases. Grok 4.7 will likely build on xAI’s recent work around software engineering, tool use, long-context reasoning, multimodal capabilities, and real-time AI assistance. Developers and AI teams should treat Grok 4.7 as an upcoming model rather than a generally available product until xAI releases official documentation. Once available, it may be relevant for coding agents, research workflows, automation, technical support, and enterprise AI applications. Built for developers and power users tracking xAI’s roadmap, Grok 4.7 represents a likely next-stage model for advanced reasoning and agentic productivity.
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    DeepSeek-V4-Flash
    DeepSeek-V4-Flash is a high-efficiency Mixture-of-Experts (MoE) language model designed for fast, scalable reasoning and text generation. It features 284 billion total parameters with 13 billion activated parameters, delivering strong performance while optimizing computational cost. The model supports an extensive context window of up to one million tokens, enabling it to process large documents and complex workflows with ease. Its hybrid attention architecture enhances long-context efficiency by reducing memory and compute requirements. Trained on over 32 trillion tokens, DeepSeek-V4-Flash demonstrates solid capabilities across knowledge, reasoning, and coding tasks. It is designed for scenarios where speed and efficiency are critical, offering a balance between performance and resource usage. The model also supports multiple reasoning modes, allowing users to adjust between faster outputs and deeper analysis.
    Starting Price: $0.14 per 1M tokens (input)
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    Qwen3.8-2.4T-A95B
    Qwen3.8-2.4T-A95B is the largest open model in the Qwen3.8 family, bringing Qwen-Max-class capabilities to an open release. Built on the architectural foundation of Qwen3.5, it delivers substantial improvements across coding, professional work, research, and long-horizon agentic tasks, with a focus on carrying complex, multi-step work through to completion more reliably. The causal language model uses a mixture-of-experts architecture with 2.4 trillion total parameters and 95 billion activated parameters, including 512 experts with 10 routed and one shared expert active at a time. It supports a native context length of 262,144 tokens that can be extended to approximately 1.01 million tokens. Agent execution is strengthened through better autonomous planning and improved handling of environment feedback, while broader compatibility with popular agent harnesses and development tools simplifies integration into existing stacks.
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    Qwen3.8-Flash-Next
    Qwen3.8-Flash-Next is an open-weight multimodal Mixture-of-Experts model and an early preview of the architecture planned for Qwen4. It systematically upgrades attention, residual connections, embeddings, and optimization to improve capability, computational efficiency, model capacity, and training stability. Its hybrid architecture combines Gated DeltaNet, which efficiently compresses historical information, with Qwen Sparse Attention, which selects important context at the micro-block level to reduce attention and indexing costs on long sequences. Gated Residual widens the residual stream into four branches and dynamically controls information flow across layers, while N-gram Embedding adds large-scale local-pattern memory with very little extra per-token computation and can be offloaded to host memory. The model uses a 125B-parameter main network plus 51B N-gram embedding parameters, while activating only 6B parameters per token.
    Starting Price: $2 per 1M (input)
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    Seed2.1 Turbo

    Seed2.1 Turbo

    ByteDance

    Seed2.1 Turbo is a next-generation AI productivity model designed to execute complex real-world tasks with strong general-agent, coding, and multimodal capabilities. It goes beyond one-off answers by carrying multi-step workflows toward defined goals and producing practical, usable outcomes across tools, environments, and interaction modes. For professional work and everyday consultation, it can support project planning, document and file processing, information analysis, solution design, content planning, tool use, and results consolidation. It also handles teaching, office, and research scenarios such as generating lesson-plan slides, analyzing complex spreadsheets, and producing industry reports. In software engineering, Seed2.1 Turbo supports end-to-end delivery across requirement analysis, feature implementation, bug fixing, environment setup, terminal usage, and result validation, while understanding codebase architecture, dependencies, and business logic to coordinate changes.
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    OpenAI Astra
    OpenAI Astra is an upcoming frontier AI model concept designed for advanced reasoning, multimodal understanding, agentic workflows, and long-horizon work. The model would be positioned to help users move from simple prompts to complete, high-quality deliverables across coding, research, business analysis, creative production, and knowledge work. Astra would combine text, image, document, voice, and tool-based capabilities into a more unified AI experience. It would be built for complex tasks that require planning, execution, verification, and iteration across multiple steps. Developers and teams could use Astra to power AI agents, productivity tools, coding assistants, research systems, and enterprise applications. As a next-generation OpenAI model concept, Astra would represent a shift toward AI systems that can reason, act, and collaborate across real-world workflows.
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    SWE-1.7

    SWE-1.7

    Cognition

    SWE-1.7 is Cognition’s frontier software engineering model designed to deliver high intelligence at a lower rollout cost. The model is optimized for long-horizon agentic coding tasks, including debugging, feature implementation, codebase exploration, migrations, terminal workflows, and multilingual software engineering. SWE-1.7 was trained from a Kimi K2.7 base using large-scale reinforcement learning improvements across infrastructure, data quality, training stability, self-compaction, and long-running task execution. It is built to explore codebases thoroughly, probe edge cases, identify hidden requirements, and produce more complete end-to-end solutions. The model is available in Devin across web, desktop, and CLI through Cerebras at very high serving speeds. SWE-1.7 is positioned for developers and engineering teams that need cost-efficient frontier-level coding intelligence for complex real-world software work.
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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 3.8 Flash Cyber
    Gemini 3.8 Flash Cyber is Google’s most capable cybersecurity model, providing frontier-level performance in vulnerability detection and automated patching with the speed needed for quick iteration. It is designed specifically for trusted defenders and is available through the Fairwind Program. On CyberGym, a standard industry benchmark for finding vulnerabilities, the model demonstrates frontier-level autonomous vulnerability discovery and surpasses both Gemini 3.5 Flash Cyber and significantly larger frontier models. Google also evaluated it on an internal benchmark covering complex codebases across 20 programming languages, where it achieved a success rate exceeding 70% in discovering a wide range of vulnerabilities. Gemini 3.8 Flash Cyber prioritizes vulnerability fixing over offensive capabilities such as exploitation, equipping defenders with expert capabilities that can help them maintain an advantage over attackers.