Loading the catalogue…
Loading the catalogue…
OpenAI's flagship closed-weight reasoning model with a 1.05M-token context window and mandatory reasoning on every request.
Anthropic's frontier reasoning model with a 1M-token context window, always-on adaptive reasoning, and native text-and-image input.
xAI's closed-weight, reasoning-tuned model for long-running agentic coding and research, with a 500K-token context window and configurable reasoning depth.
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.
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.
Anthropic's frontier reasoning model with a 1M-token context window, built for complex agentic workflows, graduate-level analysis, and long-context tasks.
Google DeepMind's Flash-tier multimodal model with a 1M-token context window and always-on, effort-adjustable reasoning for text, image, video, audio, and file inputs.
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.
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.
Google DeepMind's open-weight, multimodal Mixture-of-Experts model with a 262K-token context window, tuned for interactive-latency, moderate-complexity tasks.
Google DeepMind's open-weights 30.7B dense multimodal model with a 256K-token context window and optional chain-of-thought thinking, instruction-tuned for long-context and multimodal tasks.
OpenAI's efficient GPT-5.4 mini instruct model, built for coding and agentic workloads with optional reasoning depth and a 400K-token multimodal context window.
OpenAI's configurable chain-of-thought reasoning model with a 1M-token context window and native text, image, and file input.
Google's frontier reasoning model with a 1M-token context window, mandatory chain-of-thought inference, and full multimodal input for long-horizon, complex tasks.
A hybrid-reasoning Claude model from Anthropic with a 1M-token context window, selectable reasoning effort, and tool calling for coding, research, and agentic work.
One of Anthropic's Claude Opus 4 models — a one-million-token context window, optional adaptive thinking, and native document understanding for reasoning-heavy and agentic work.
OpenAI's agentic coding model in the GPT-5 family, built for terminal and IDE workflows with a 400K-token context window and native tool orchestration.
Google's multimodal Flash model with a 1M+ token context and opt-in reasoning effort, built for fast Inference on complex, mixed-media tasks.
Mistral AI's open-weight flagship: a 675B-parameter (41B active) Granular MoE model with native vision input, function calling, and a 262,144-token context window, built for long-document and multimodal workflows.
Anthropic's frontier Claude Opus 4.5: a proprietary, text-and-image model built for complex coding, research, and long-document reasoning with optional extended thinking.
Anthropic's fastest Claude 4 model — built for high-throughput agentic and coding workloads, with a 200K-token context window, optional extended thinking, vision input, and strong safety benchmarks.
Anthropic's instruct-tuned Claude Sonnet 4.5 — built for agentic coding, computer-use, and long-context reasoning via the Claude API.
OpenAI's compact GPT-5 variant with tunable reasoning effort, a 400K-token context window, and multimodal input for interactive document and image tasks.
OpenAI's fastest, lightest GPT-5 tier for high-volume classification, summarisation, and short completions — 400K context, vision and file input, mandatory reasoning traces.
Google's fastest, lowest-cost Gemini 2.5 model — a multimodal instruct model with a 1M-token context window, built for realtime, high-throughput Inference.
Google's closed-weight, reasoning-tuned flagship with a 1M-token context window, multimodal input, and native tool calling.
Google DeepMind's efficiency-tier multimodal model with a 1M-token context window, optional chain-of-thought thinking, and native text, image, audio, video, and file input.
OpenAI's compact, instruction-tuned multimodal model for high-throughput, realtime-latency Inference on medium-complexity tasks.
OpenAI's 2024 multimodal flagship for fast, complex text-and-vision tasks with tool calling, structured outputs, and a 128K context window.
OpenAI's closed-weight GPT-4 Turbo brings a 128K-token context window and text+image input to complex, long-context tasks at interactive latency.
No models match your search.