Alternatives to Inkling

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

  • 1
    Gemini 4 Argon
    Gemini 4 Argon is a frontier artificial intelligence model developed by Google DeepMind for complex reasoning, software engineering, cybersecurity, and professional knowledge work. The model supports multimodal inputs, including text, images, audio, video, and PDF documents, with a unified context window of approximately one million tokens. Its advanced reasoning capabilities enable it to analyze difficult problems, maintain context across lengthy workflows, and execute multistep tasks. Gemini 4 Argon supports autonomous AI agents, code generation, application development, scientific research, and analysis of legal and financial information. Developer capabilities include function calling, code execution, structured outputs, search grounding, and preview support for computer use. The model is available through the Gemini API, Google AI Studio, Google Antigravity, and supported Gemini applications and enterprise services.
    Starting Price: $2 per 1M tokens (input)
  • 2
    Claude Sonnet 5.5
    Claude Sonnet 5.5 is Anthropic’s mid-tier Claude 5.5 model designed for fast, well-scoped everyday work, coding, and professional document creation. Anthropic says it runs more than 30% faster than Claude Sonnet 5 and typically costs up to 30% less per task while keeping the same base token pricing. The model shows major gains in agentic coding, with a 70.6% score on Terminal-Bench 4.0 and stronger performance on FrontierCode and CursorBench than its predecessor. Sonnet 5.5 also performs strongly on knowledge work, computer use, chart understanding, and long-horizon tasks, in some cases approaching Claude Opus 5.5 at higher effort settings. Anthropic positions it as especially useful for debugging, routine coding, collaboration, and producing polished documents, slides, spreadsheets, and user interfaces. Claude Sonnet 5.5 is available across Anthropic’s platforms as well as AWS, Google Cloud, and Microsoft Azure.
    Starting Price: $2 per 1M tokens (input)
  • 3
    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)
  • 4
    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.
  • 5
    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)
  • 6
    GPT-6 Astra
    GPT-6 Astra is OpenAI’s frontier AI model for computer use, software engineering, scientific research, cybersecurity, browsing, and complex professional work. It combines advanced reasoning with agentic capabilities that allow it to navigate software, use tools, conduct research, manipulate data, troubleshoot systems, and complete multistep workflows. Astra is also designed to produce polished documents, spreadsheets, presentations, websites, applications, and other business or technical artifacts while following existing templates and organizational standards. In Codex, the model introduces improved long-running context management that can preserve notes and retrieve information from earlier context windows during extended software engineering tasks. OpenAI positions Astra as its most aligned model to date, with improvements in respecting task boundaries, interpreting user intent, communicating limitations, and avoiding unauthorized actions.
    Starting Price: $10 per 1M tokens (input)
  • 7
    Claude Opus 5.5
    Claude Opus 5.5 is Anthropic’s advanced AI model for agentic coding, complex knowledge work, computer use, research, and long-running professional tasks. It is designed to handle large codebases, multi-step workflows, financial analysis, document creation, software audits, and other demanding workloads with improved efficiency over Claude Opus 5. Anthropic reports that Opus 5.5 uses fewer tokens per task, produces output more than 30% faster, and costs less to run than its predecessor. The model also improves communication quality by putting important information first, reducing unnecessary jargon, and following writing instructions more consistently. Safety enhancements include stronger prompt-injection resistance, action screening, sandboxing support, code review, behavioral alignment testing, and safeguards for high-risk cybersecurity & biology. Claude Opus 5.5 is available through Claude, Claude Code, the Claude Platform API, Amazon Web Services, Google Cloud, and Microsoft Azure.
    Starting Price: $4 per 1M tokens (input)
  • 8
    GPT-6 Luna
    GPT-6 Luna is OpenAI’s cost-efficient GPT-6 model designed for everyday professional work, coding, computer use, and agentic applications at scale. It brings many of the advances introduced with GPT-6 Astra to a faster and substantially lower-cost model while improving on GPT-5.6 Luna in capability and factual reliability. The model supports adjustable reasoning effort, allowing applications to spend more compute on harder tasks and less on simpler requests. GPT-6 Luna can handle software engineering, multi-step business workflows, computer interaction, and other tool-using tasks that benefit from low operating cost. Improved GPT-6 prompt caching helps long-running agents reuse more context, respond faster, and reduce the cost of repeated input. GPT-6 Luna is available in ChatGPT Work, Codex, the ChatGPT desktop app for Free and Go users, and the OpenAI API as gpt-6-luna.
    Starting Price: $0.10 per 1M tokens (input)
  • 9
    GPT-6 Sol
    GPT-6 Sol is an OpenAI model designed to bring GPT-6-class intelligence to professional work, coding, computer use, and agentic workflows at a lower cost than GPT-6 Astra. The model improves on GPT-5.6 Sol in factual reliability, software engineering, business automation, and long-horizon computer tasks. Developers can adjust reasoning effort depending on task complexity, allowing Sol to allocate more computation to difficult problems while using less for simpler work. GPT-6 Sol also introduces a clearer collaboration style with less jargon, fewer unnecessary details, and more concise technical communication. Improved prompt caching helps agents reuse long contexts more efficiently while reducing latency and cached-input costs. GPT-6 Sol is available through ChatGPT Work, Codex, and the OpenAI API as gpt-6-sol.
    Starting Price: $2 per 1M tokens (input)
  • 10
    Grok 4.7

    Grok 4.7

    SpaceXAI

    Grok 4.7 is a frontier AI model from SpaceXAI designed for coding, professional knowledge work, and longer-running agentic tasks. The model uses a larger base architecture than Grok 4.6 and was trained with an extended reinforcement learning process focused on difficult tasks that can take many hours to complete. Grok 4.7 improves self-verification, long-context management, conversational performance, and general knowledge work while adding native understanding of the Grok Bot harness. It is designed for software engineering, terminal-based work, document creation, presentations, legal tasks, electrical engineering, clinical reasoning, and other professional workflows. The model also introduces a new safeguard stack focused on jailbreak resistance, risky cybersecurity requests, and other dual-use domains while preserving utility for legitimate work. Grok 4.7 is available through Grok Build, Cursor, the Grok API, third-party coding harnesses, model routers, and cloud platforms.
    Starting Price: $2 per 1M tokens (input)
  • 11
    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)
  • 12
    Muse Wonder
    Muse Wonder is a frontier artificial intelligence model developed by Meta for personal assistance, professional workflows, software development, and autonomous agent tasks. The model combines Active Memory, which retrieves relevant information from previous conversations, with Active Focus, which supports sustained execution of complex, multistep assignments. Muse Wonder can assist with research, document analysis, financial and legal information, software engineering, and business process automation. Its agentic capabilities enable it to work across applications, use contextual information, adapt to obstacles, and request clarification or approval when necessary. The model supports coding activities ranging from small application development to complex software projects involving repeated testing and revision. Muse Wonder is available through the Meta Model API and Muse Code, with additional integration into Meta's Muse assistant planned for future releases.
    Starting Price: $4 per 1M tokens (input)
  • 13
    GPT-6.1 Sol
    GPT-6.1 Sol is an OpenAI model designed to deliver near-GPT-6 Astra intelligence at substantially lower cost across coding, professional work, computer use, scientific research, and agentic workflows. It improves on GPT-6 Sol across complex tasks such as software engineering, document analysis, multi-step business automation, and computer interaction. On DeepSWE v1.1, GPT-6.1 Sol matches GPT-6 Astra at roughly one-fifth of the cost while exceeding GPT-6 Sol's best score by 6.4 percentage points at a lower reasoning effort. The model also improves computer use, outperforming GPT-6 Sol by seven percentage points on the OSWorld 2.0 offline set at maximum reasoning effort while costing less than half as much per task. GPT-6.1 Sol provides improved factuality and alignment, including greater transparency about limitations and stronger adherence to user instructions during agentic tasks. It is available through ChatGPT Work, Codex, and the OpenAI API.
    Starting Price: $2 per 1M tokens (input)
  • 14
    MiMo-V2.6-Pro

    MiMo-V2.6-Pro

    Xiaomi Technology

    MiMo-V2.6-Pro is Xiaomi MiMo’s most capable open-source omnimodal AI model, built for coding, general agent workflows, visual tasks, research, and multimodal creation. The model combines strong software engineering capabilities with computer use, 3D spatial reasoning, visual perception, and tool use for complex multi-step work. MiMo-V2.6-Pro can build interactive 3D environments, generate Blender models, create frontend interfaces and presentations, and coordinate agents to refine outputs through visual feedback. It also supports research workflows such as literature review, computational experimentation, materials discovery, and formal mathematical proof development. Xiaomi trained the model with large-scale reinforcement learning across coding, general agents, visual tasks, and cybersecurity environments and has open-sourced the technical report, training environments, and RL code.
  • 15
    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)
  • 16
    MiMo-V2.6-Flash

    MiMo-V2.6-Flash

    Xiaomi Technology

    MiMo-V2.6-Flash is an open-source, natively omnimodal AI model from Xiaomi MiMo designed to balance intelligence, efficiency, and cost. The model supports coding, general agent workflows, visual reasoning, computer use, automation, and multimodal creative tasks. Its capabilities extend beyond software engineering into frontend design, presentation creation, 3D modeling, interactive world generation, video production, and embodied simulation. Xiaomi trained MiMo-V2.6-Flash with large-scale reinforcement learning across coding, general agent, visual, and cybersecurity tasks, completing roughly 750,000 training trajectories. The model is positioned as the more cost-efficient member of the MiMo-V2.6 family while retaining strong performance across software engineering, tool use, automation, and visual coding benchmarks. MiMo-V2.6-Flash is available through MiMo Desktop, AI Studio, MiMo Code, the Xiaomi MiMo API Platform, OpenRouter, and the open-source MiMo-V2.6 release.
  • 17
    SWE-2

    SWE-2

    Cognition

    SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.
    Starting Price: $20/month
  • 18
    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)
  • 19
    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)
  • 20
    Claude Haiku 5.5
    Claude Haiku 5.5 is an Anthropic AI model designed for high-volume, latency-sensitive workloads such as classification, routing, extraction, and subagent tasks. The model supports adaptive thinking, allowing it to determine when and how much reasoning to perform based on the request. Developers can use the effort parameter to balance response quality against speed and cost, while adaptive thinking is enabled by default. Claude Haiku 5.5 provides a 1 million token context window and supports outputs of up to 128,000 tokens, increasing from the 200,000-token context window and 64,000-token output limit of Claude Haiku 4.5. It also supports browser use through the Claude API and Google Cloud for workflows that require interaction with web-based environments. Claude Haiku 5.5 uses Anthropic's newer tokenizer introduced with Claude 4.7 and later models, which results in the same text using approximately 30% more tokens than with Claude Haiku 4.5.
    Starting Price: $0.10 per 1M tokens (input)
  • 21
    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)
  • 22
    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)
  • 23
    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.
  • 24
    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
  • 25
    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)
  • 26
    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)
  • 27
    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.
  • 28
    Laguna S 2.1
    Laguna S 2.1 is an open weight agentic coding model designed to pursue longer-horizon work and make effective use of reasoning. It uses a 118-billion-parameter Mixture-of-Experts architecture with 8 billion active parameters per token and supports a context window of up to one million tokens in both thinking and no-thinking modes. Its compact active size makes it suitable for complex work on local machines while remaining competitive with models many times larger on terminal, software-engineering, codebase-question-answering, and tool-use benchmarks. Laguna S 2.1 is built to keep working through difficult tasks with greater persistence, verification, and willingness to backtrack instead of declaring success too early. In demonstrated runs, it built and validated a browser rendering engine from an empty folder, optimized an agent harness for faster execution and substantially lower memory allocation, and completed extended mathematical research using the tools in its environment.
  • 29
    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
  • 30
    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)
  • 31
    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)
  • 32
    Kimi K2.7 Code

    Kimi K2.7 Code

    Moonshot AI

    Kimi K2.7 Code is an open-source, coding-focused agentic AI model developed by Moonshot AI for long-horizon software engineering tasks. It is designed to improve coding performance, agent workflows, and real-world development assistance compared with earlier Kimi K2 versions. The model supports a 256K context window, making it useful for working with large codebases, long technical documents, and complex multi-step programming tasks. Kimi K2.7 Code is available through Kimi Code and API access, with OpenAI- and Anthropic-compatible options for easier integration into developer workflows. It is also listed on Hugging Face and supports deployment through inference engines such as vLLM, SGLang, and KTransformers. With improved agentic capabilities, long-context support, and reduced thinking-token usage compared with K2.6, Kimi K2.7 Code gives developers a flexible open-source option for AI-assisted coding.
  • 33
    Nemotron 3 Ultra
    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.
  • 34
    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)
  • 35
    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)
  • 36
    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.
    Starting Price: $0.50/M input
  • 37
    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.
  • 38
    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.
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    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)
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    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)
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    MiMo-V2.5-Pro

    MiMo-V2.5-Pro

    Xiaomi Technology

    Xiaomi MiMo-V2.5-Pro is an advanced open-source AI model designed to handle complex, long-horizon tasks with strong agentic capabilities. It features a Mixture-of-Experts architecture with over one trillion parameters and a large context window of up to one million tokens. The model is built to perform sophisticated reasoning, coding, and problem-solving across extended workflows. It demonstrates high performance on benchmark tests related to software engineering, reasoning, and general intelligence. MiMo-V2.5-Pro can autonomously complete complex projects, such as building full software systems or optimizing engineering designs. It uses hybrid attention mechanisms to balance efficiency and performance across long contexts. The model is also optimized for token efficiency, reducing computational cost while maintaining strong results. By combining scalability, efficiency, and advanced reasoning, MiMo-V2.5-Pro represents a major step forward in open-source AI models.
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    MiMo-V2.6-Pro-UltraSpeed

    MiMo-V2.6-Pro-UltraSpeed

    Xiaomi Technology

    MiMo-V2.6-Pro-UltraSpeed is a high-speed serving mode for Xiaomi MiMo’s flagship MiMo-V2.6-Pro model, designed for latency-sensitive AI workloads. It delivers the same underlying model quality as MiMo-V2.6-Pro while providing output speeds of up to 20 times faster. The model supports coding, agentic automation, multimodal reasoning, visual design, research, and other complex tool-using workflows. Its capabilities include software engineering, frontend creation, presentation design, 3D modeling, interactive world generation, computer use, and multimodal analysis. MiMo-V2.6-Pro-UltraSpeed is intended for real-time applications where the capabilities of MiMo-V2.6-Pro are needed with substantially faster generation. It is available through MiMo Desktop and the Xiaomi MiMo API Platform.
    Starting Price: $4.35 per 1 million tokens inp
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    K2 Horizon

    K2 Horizon

    Institute of Foundation Models

    K2 Horizon is a connected fleet of six open models spanning 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B, designed to deliver strong performance across reasoning, mathematics, coding, agentic tasks, and general capabilities. The models share core architecture, vocabulary, training methodology, interfaces, evaluation infrastructure, and deployment tooling, making it easier to move between sizes and route workloads dynamically. The 375B-A23B model is the fleet’s most capable option for complex reasoning, software engineering, research, and long-horizon agentic work, while the 32B and 36B-A4B models target powerful local deployment. The 36B-A4B model introduces Mixture-of-Value Attention, combining sparse attention with Mixture-of-Experts layers to activate about 4 billion parameters per token while approaching the performance of the dense 32B model.
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    Holo4

    Holo4

    H Company

    Holo4 is a family of generalist agentic AI models from H Company designed to operate software across graphical interfaces, code environments, MCP servers, APIs, desktop applications, the web, and mobile devices. The family includes a 27B dense model and a 35B-A3B Mixture-of-Experts model with 3B active parameters, both supporting a 256K context window. Unlike agents optimized around a single interface, Holo4 can click and type on screens, write and execute code, and call MCP or API tools depending on what a task requires. The models were trained with supervised fine-tuning and reinforcement learning on agentic workflows spanning desktop, web, MCP/API, mobile, coding, multimodal reasoning, and GUI grounding. Holo4 27B achieved 85.2% on OSWorld at a reported cost of $0.08 per task, while Holo4 35B-A3B scored 80.8% at $0.05 per task in H Company's evaluation.
    Starting Price: $0.40 per 1M tokens (input)
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    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)
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    OpenAI Bel
    OpenAI Bel is the reported codename of an unreleased artificial intelligence foundation model associated with OpenAI. Unofficial reports describe it as a large-scale pretraining project intended to support future generations of AI models. The project has been linked in speculative reporting to OpenAI's Astra model family and potential successors to GPT-6. Some sources claim that Bel contains more than 10 trillion parameters, although this figure has not been independently verified. OpenAI has not published official technical specifications, benchmark results, or documentation confirming the project's capabilities. Bel is not currently available as a publicly documented model through ChatGPT or the OpenAI API.
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    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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    Nemotron 3 Super
    Nemotron-3 Super is part of NVIDIA’s Nemotron 3 family of open models designed to enable advanced agentic AI systems that can reason, plan, and execute multi-step workflows across complex environments. The model introduces a hybrid Mamba-Transformer Mixture-of-Experts architecture that combines the efficiency of state-space Mamba layers with the contextual understanding of transformer attention, allowing it to process long sequences and complex reasoning tasks with high accuracy and throughput. This architecture activates only a subset of model parameters for each token, improving computational efficiency while maintaining strong reasoning capabilities and enabling scalable inference for large workloads. Nemotron-3 Super contains roughly 120 billion parameters with around 12 billion active during inference, accelerating multi-step reasoning and collaborative agent interactions across large contexts.
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    Qwen3.7-Max
    Qwen3.7-Max is Qwen’s latest proprietary model designed for the agent era, built to be a versatile agent foundation that is equally capable of writing and debugging code, automating office workflows, and sustaining autonomous browser sessions over long horizons. It reaches frontier-level coding performance, with stronger results across software engineering, terminal tasks, GUI grounding, web browsing, and agentic tool use. Qwen3.7-Max is designed to reduce the gap between model intelligence and real agent execution by supporting planning, long-context reasoning, reliable function calling, and multi-step task completion across complex workflows. It also strengthens multimodal and document-oriented work through Qwen Studio, which supports chatbot interaction, image and video understanding, image generation, document processing, presentation generation, coding assistance, deep research, and web development.
    Starting Price: Free
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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.