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DeepSeek's vision-capable sparse MoE model for text and image input, with a 1M-token context window and MIT-licensed open weights.
Anthropic's low-latency multimodal model featuring a 1,000,000-token context window and configurable reasoning effort.
Mistral AI's 1.05T MoE frontier multimodal model with 52B active parameters, 512K context, and configurable reasoning traces.
Google's closed-weight Gemini 4 Argon is a multimodal reasoning model with configurable thinking levels and a 1,048,576-token context window.
OpenAI's closed-weight reasoning model with a 1,050,000-token context window, mandatory configurable reasoning effort and native hosted tools, sitting between GPT-6 Sol and the GPT-6 Astra flagship.
Anthropic's closed-weight Sonnet-class reasoning model with a 1M-token context window, always-on adaptive thinking, and configurable effort levels.
Anthropic's flagship hybrid reasoning model, with always-on adaptive thinking and a 1M-token context window for deep analytical and coding work.
OpenAI's fast, cost-efficient GPT-6 model for high-volume chat, classification, and lightweight agentic tasks, with dialable reasoning effort and a 1.05M-token context window.
OpenAI's mid-tier reasoning model with configurable effort levels, a 1.05M-token context window, and text+image input for coding and agentic workflows.
Xiaomi's MIT-licensed efficiency-tier omnimodal reasoning model: a 309B/15B sparse MoE with a 1M-token context, native image, video and audio understanding, and a caller-controlled thinking switch.
xAI's reasoning-first flagship with a 500K-token context window, built for deep coding, agentic, and long-document knowledge work.
Xiaomi's open-weight 1.02T-parameter omnimodal reasoning model with a 1M-token context, accepting text, image, video and audio input and returning text.
DeepSeek's unified multimodal MoE model combining native text+image input, a 1M-token context window, and a controllable reasoning-effort slider in one Flash-tier endpoint.
OpenAI's flagship closed-weight reasoning model with a 1.05M-token context window and mandatory reasoning on every request.
Google's reasoning-tuned Flash-tier model for fast coding, agentic, and multi-step reasoning tasks with a million-token multimodal context window.
Anthropic's frontier reasoning model with a 1M-token context window, always-on adaptive reasoning, and native text-and-image input.
Z.ai's natively multimodal Mixture-of-Experts model with a 1M+ token context window and mandatory reasoning.
Z.ai's flagship 743B-parameter MoE model, open-weighted and post-trained for complex coding and long-horizon agentic tasks, with a 1M-token context window.
DeepSeek's open-weight, MIT-licensed V4 Pro reasoning model — a large mixture-of-experts system with a million-token context window and selectable reasoning effort for long, multi-step tasks.
xAI's closed-weight, reasoning-tuned model for long-running agentic coding and research, with a 500K-token context window and configurable reasoning depth.
Alibaba/Qwen's largest open-weight release: a 2.4T-parameter mixture-of-experts model with mandatory reasoning and a 262K-token context window.
Alibaba's open-weight, always-reasoning Qwen3.8 Max-class mixture-of-experts model with a 262K-token native context window.
An open-weights, low-latency NVIDIA reasoning and agentic model with a toggleable chain-of-thought mode and a hybrid Mamba-2/MoE/Attention architecture.
A million-token-context, mixture-of-experts reasoning model from DeepSeek with adjustable thinking effort, served on the Stav Platform via Fireworks AI.
Anthropic's frontier reasoning model with a 1M-token context, adjustable reasoning effort, and multimodal input for code, research, and long-document work.
Google's fast, cost-focused Gemini 3.5 model with a million-token context window, mandatory configurable reasoning, and multimodal text, image, audio, and video input.
Google's reasoning-tuned Flash model: multimodal input, a million-token-plus context window, and always-on chain-of-thought for agentic, long-horizon tasks.
Moonshot AI's open-weights, always-reasoning 2.8T MoE flagship with a 1M-token context, native tool use, and multimodal input.
Thinking Machines Lab's first open-weight model: a 975B/41B-active MoE transformer with multimodal input, a 1M-token context window, and configurable reasoning effort.
OpenAI's fast, cost-efficient GPT-5.6 tier for high-volume chat, classification, and lightweight agentic tasks with a 1.05M-token context window.
OpenAI's flagship GPT-5.6 reasoning model for agentic coding, cybersecurity, and long-horizon analysis, with a 1.05M-token context window.
OpenAI's balanced GPT-5.6 model, offering a 1.05M-token context window and configurable reasoning effort for mid-complexity coding and document tasks.
xAI's proprietary reasoning model with a 500,000-token context window, mandatory configurable reasoning effort, and text and image input.
Anthropic's adaptive-reasoning Sonnet-class model with a 1M-token context window, strong Design Arena coding and UI results, and always-on reasoning selectable from low to max effort.
Z.ai's flagship open-weights reasoning and agentic-coding model, with a 1M-token context window and MIT-licensed weights.
Moonshot AI's 1T-parameter open-weights MoE coding and agentic model with mandatory extended thinking and a 262,144-token context window.
Anthropic's frontier Mythos-class model with always-on adaptive reasoning and a one-million-token context window, built for deep code and research analysis rather than real-time chat.
NVIDIA's flagship 550B/55B-active Nemotron 3 Ultra reasoning model, open-weighted under OpenMDW-1.1 with a 256K-token context window.
An open-weight 428B-parameter (~23B active) MoE model from MiniMax with a 1M-token context window, multimodal input, and a configurable thinking mode, suited to long-context, agentic, and coding-assist workloads.
xAI's agentic coding model: a 256K-context, tool-calling assistant with mandatory step-by-step reasoning, built for multi-step debugging and MCP orchestration.
Anthropic's frontier reasoning model with a 1M-token context window, built for complex agentic workflows, graduate-level analysis, and long-context tasks.
Dense 128B open-weight multimodal model from Mistral AI with a 256K context and optional reasoning.
Google's fast, cost-optimised multimodal Gemini model with a million-token context window, built for high-throughput text, image, audio, video, and file input.
xAI's reasoning model with a 1M-token context window and configurable reasoning effort, on by default.
OpenAI's long-context instruct model, built for complex multi-step reasoning, long-document analysis, and tool orchestration across a 1M+ token context window.
Anthropic's frontier-tier closed-weight instruct model with a one-million-token context window, built for complex, long-horizon reasoning and coding rather than real-time interaction.
Z.ai's 754B-parameter open-weight MoE model with integrated reasoning, built for long-horizon agentic engineering and state-of-the-art coding benchmark performance.
Google DeepMind's open-weight, multimodal Mixture-of-Experts model with a 262K-token context window, tuned for interactive-latency, moderate-complexity tasks.