Models

Anthropic's most capable publicly-available model. Designed for ambitious long-running agentic tasks — software engineering, scientific research, and complex knowledge work. Features mandatory adaptive thinking, 1M token context window, 128K output capacity, and all effort levels including xhigh and max. Priced at $10/$50 per million tokens.

Anthropic's latest Opus model for complex agentic coding and enterprise work — approaching Claude Fable 5's capability at half the price ($5/$25 per million tokens). Features a 1M token context window, 128K output capacity, adaptive thinking on by default with full effort control (low through max), and stronger self-verification and error recovery so it needs less back-and-forth. Knowledge cutoff May 2026.

Previous-generation Opus model. ~4x more reliable code review, top Super-Agent benchmark (only model to complete every case end-to-end), and 84% on Online-Mind2Web computer use. Features 1M token context window, 128K output capacity, adaptive thinking with effort control, and priority service tier. Anthropic recommends Claude Opus 5 for new work.

Previous-generation Opus model. Features 1M token context window with new tokenizer, 128K output capacity, adaptive thinking (only supported thinking mode), high-resolution image support (2576px / 3.75MP), task budgets, and xhigh effort level. Strong at complex reasoning, agentic coding, knowledge work, and vision tasks; Anthropic recommends Claude Opus 5 for new work.

Anthropic's flagship balanced model with near-Opus level performance at mid-tier pricing. Features 1M token context window, 128K output capacity, exceptional coding capabilities (79.6% on SWE-bench), and advanced computer use (72.5% on OSWorld). Ideal for complex agents, long-context reasoning, and production workflows.

Anthropic's latest balanced model with adaptive thinking on by default. Features 1M token context window, 128K output capacity, stronger coding and agentic capabilities, and improved vision. Uses a new tokenizer and the effort parameter for reasoning control. Introductory pricing at $2/$10 per million tokens through August 2026.

Anthropic's smart model for complex agents and coding tasks. Offers the best balance of intelligence, speed, and cost for most use cases, with exceptional performance in coding and agentic workflows.

Anthropic's most intelligent model with breakthrough capabilities. Features 1M token context window, 128K output capacity, adaptive thinking for optimal reasoning, and agent teams for complex workflows. Best for enterprise agents, production coding, and sophisticated problem-solving.

Anthropic's premium model combining maximum intelligence with practical performance. Delivers state-of-the-art coding capabilities and frontier performance for production code, sophisticated agents, and complex tasks.

Anthropic's fastest model with near-frontier intelligence. Matches Sonnet 4's performance on coding, computer use, and agent tasks while being optimized for speed and cost-efficiency.

Legacy model. Anthropic recommends migrating to Claude 4.5 models for improved performance.

Legacy model. Anthropic recommends migrating to Claude 4.5 models for improved performance.

Legacy model. Anthropic recommends migrating to Claude 4.5 models for improved performance.

Fast and efficient model from Anthropic's Claude 3.5 series, designed for quick, straightforward tasks.

Anthropic's fastest, most compact Claude 3 model for near-instant responsiveness. Answers simple queries and requests with unmatched speed.

OpenAI's flagship frontier model for complex professional work. Official API docs position Sol as the default starting point for complex reasoning and coding. Features a 1.05M token context window, 128K max output, image understanding, and max reasoning effort. The OpenAI API also exposes the alias 'gpt-5.6' for this model family default. OpenAI documents additional native tools for this family, but Aisle currently exposes the verified web search path only.

OpenAI's GPT-5.6 model that balances intelligence and cost. Features a 1.05M token context window, 128K max output, image understanding, and max reasoning effort. OpenAI documents additional native tools for this family, but Aisle currently exposes the verified web search path only.

OpenAI's GPT-5.6 model optimized for cost-sensitive, high-volume workloads. Features a 1.05M token context window, 128K max output, image understanding, and max reasoning effort. OpenAI documents additional native tools for this family, but Aisle currently exposes the verified web search path only.

OpenAI's most capable frontier model. Features 1.05M token context window, native compaction for longer agent trajectories, 33% fewer errors than GPT-5.2, and 18% fewer response-level errors. First mainline model with computer-use capabilities.

OpenAI's maximum-capability model for the most demanding professional workloads. Features 1.05M context window with restricted reasoning options (medium through xhigh) for consistently deep analysis.

OpenAI's first fully retrained base model since GPT-4.5. Features 1.05M token context window, ~40% improved token efficiency, and reasoning defaulted to 'low' (rather than 'none') for stronger out-of-the-box answers. Same reasoning controls as GPT-5.4 — 'none' through 'xhigh' available.

OpenAI's maximum-capability model in the GPT-5.5 family. Features 1.05M token context window with restricted reasoning options (medium through xhigh) for consistently deep analysis. Same parameter shape as GPT-5.4 Pro.

OpenAI's most capable model for professional knowledge work, combining maximum reasoning capabilities with strong performance on complex, multi-step tasks across spreadsheets, presentations, coding, and long contexts.

OpenAI's advanced model for complex knowledge work. Excels at building spreadsheets and presentations, writing code, interpreting images, and working with long contexts. Performs at or above human expert level on well-specified knowledge work tasks.

Fast variant of GPT-5.2 optimized for responsive professional tasks. Delivers GPT-5.2's capabilities with reduced latency for real-time applications.

Fast variant of GPT-5.3 optimized for everyday tasks. Delivers responsive, low-latency performance for real-time applications and conversational workflows.

OpenAI's most capable agentic coding model. Combines Codex and GPT-5 training stacks for best-in-class code generation, reasoning, and general-purpose intelligence. 25% faster than its predecessor. Optimized for long-running agentic coding tasks.

OpenAI's breakthrough model with significant improvements in math, coding, visual perception, and health. 94.6% on AIME 2025, 74.9% on SWE-bench Verified. ~45% less likely to hallucinate than GPT-4o.

Efficient variant of GPT-5 for cost-effective intelligent tasks. Balances strong performance with reduced computational requirements.

Ultra-efficient GPT-5 model optimized for high-volume, cost-sensitive applications. The fastest and most affordable option in the GPT-5 series.

Iterative improvement of GPT-5 with more conversational style, improved instruction following, and adaptive reasoning capabilities.

OpenAI model with major improvements in coding and instruction following. Completes 54.6% of SWE-bench Verified tasks vs 33.2% for GPT-4o. Features 1M token context window and improved long-context comprehension.

Balanced small model matching GPT-4o intelligence at nearly half the latency and 83% lower cost. Features 1M token context window with strong coding and instruction-following performance.

OpenAI's fastest and cheapest model with 1M token context window. Scores 80.1% on MMLU. Optimized for high-volume, low-latency applications requiring basic intelligence.

Fast, affordable small model for focused tasks. Accepts text and image inputs with structured outputs. Optimized for cost-effective intelligent processing.

OpenAI reasoning model trained with reinforcement learning to perform complex reasoning tasks. Designed to think deeply before responding.

OpenAI's most powerful reasoning model. Pushes the frontier across coding, math, science, and visual perception. 20% fewer major errors than o1 on real-world tasks. First reasoning model with agentic tool use including web search and image understanding.

Fast, cost-efficient reasoning model optimized for high-volume STEM tasks. Best-performing benchmarked model on AIME 2024 and 2025. Supports higher usage limits than o3 for throughput-sensitive workloads.

Small reasoning model optimized for science, math, and coding tasks. Offers efficient complex reasoning at lower computational cost.

OpenAI's most advanced image generation model. Creates high-quality images from text prompts with improved accuracy and detail. Supports 1024x1024 resolution.

OpenAI's latest image generation model with improved quality and instruction following.

Google's most capable model for multimodal understanding and advanced agentic tasks. Successor to Gemini 3 Pro Preview with improved reasoning across text, images, video, audio, and PDFs.

Google's most balanced model built for speed, scale, and frontier intelligence. Default model across several Google surfaces with strong coding and state-of-the-art reasoning. Supports thinking, structured outputs, and search grounding across text, images, video, audio, and PDFs.

Google's fastest and most cost-efficient Gemini 3.1 model. Optimized for high-throughput, low-latency applications with strong reasoning across text, images, video, audio, and PDFs.

Google's state-of-the-art thinking model, capable of reasoning over complex problems in code, math, and STEM. Excels at analyzing large datasets, codebases, and documents using long context windows. Scheduled for retirement October 16th, 2026.

Google's best model in terms of price-performance, offering well-rounded capabilities. Optimized for large-scale processing and low-latency, high-volume tasks with thinking capabilities. Scheduled for retirement October 16th, 2026.

Google's fastest flash model optimized for cost-efficiency and high throughput. Ultra-fast processing designed for maximum efficiency in high-volume applications. Scheduled for retirement October 16th, 2026.

Google's latest image generation model.

Google's highest quality image generation model.

xAI's latest flagship reasoning model (March 2025). Strong at complex multi-step tasks, coding, and analysis. Supports X search and web search. 256K context.

xAI's latest flagship model without reasoning overhead (March 2025). Faster responses for direct tasks. Supports X search and web search. 256K context.

xAI's Grok 4.20 optimised for multi-agent orchestration (March 2025). Best suited for tasks involving coordination across multiple AI agents.

xAI's fast reasoning model. Balances depth with low latency for production reasoning workloads. Supports X search and web search. 256K context.

xAI's fastest grok-4 generation model. Minimal latency, direct responses without reasoning overhead. Supports X search and web search. 256K context.

xAI's most capable model with X search support

Grok 4 pinned to the July 2025 release

xAI's most powerful model with deep reasoning capabilities. Excels at complex analysis, coding, and multi-step problem solving with a 1M token context window.

xAI's high-speed model built for low-latency production workloads. Delivers rapid responses while maintaining strong reasoning capabilities. 1M token context window.

xAI's compact, cost-efficient reasoning model. Supports reasoning_effort control for balancing speed vs depth. Ideal for high-volume tasks.

xAI's fastest compact model. Same capabilities as Grok 3 Mini with optimised infrastructure for minimal latency. Supports reasoning_effort control.

xAI's multimodal model with image understanding. Accepts JPEG and PNG images up to 20MB alongside text for richer, context-aware responses.

xAI's image generation model.

xAI's premium image generation model with enhanced quality.

MoonshotAI's Kimi K2.5 model via OpenRouter. Features massive 262K token context window for handling very long documents and conversations.

Writer's Palmyra X5 model via OpenRouter. Enterprise AI agent model with 1.04M token context window. Features novel transformer architecture and hybrid attention mechanisms for faster inference and expanded memory, optimized for processing large enterprise data volumes.

MiniMax's M2.1 model via OpenRouter. Consistently ranks in top-10 across benchmarks with strong performance in reasoning and coding tasks. Features 196K context window.

Xiaomi's MiMo V2 Flash model via OpenRouter. Ranked #1 on SWE-bench benchmark with 309B total parameters and 15B active parameters. Features hybrid-thinking toggle for optimal performance in coding tasks.

Mistral's Devstral 2 model via OpenRouter. 123B-parameter dense transformer model specializing in agentic coding across multiple files. Features 262K context window for handling complex codebases.

Amazon's Nova 2 Lite model via OpenRouter. Multimodal model supporting text, image, video, and file inputs. Excels at document processing, video information extraction, code generation, and multi-step agentic workflows. Features 1M token context window.

xAI's best agentic tool calling model via OpenRouter. Features 2 million token context window, exceptional for customer support, research, and complex agentic workflows. Supports reasoning toggle and web search.

Amazon's Nova Premier model via OpenRouter. Flagship AWS model with 1M token context window designed for complex reasoning tasks. Multimodal support for text and image inputs. Can be used as a teacher model for custom distillation.

Mistral AI's mid-tier model via OpenRouter. Balances performance and cost, suitable for a wide range of tasks requiring solid reasoning and generation capabilities.

Mistral AI's specialized coding model via OpenRouter. Optimized for code generation, completion, and technical tasks with exceptional programming capabilities across multiple languages.

Google's state-of-the-art thinking model via OpenRouter. Capable of reasoning over complex problems in code, math, and STEM with long context support. Scheduled for retirement June 17, 2026.

Alibaba's largest open-source Qwen3 model via OpenRouter with 235B parameters. Apache 2.0 licensed with exceptional multilingual capabilities and strong performance across diverse tasks.

Alibaba's balanced Qwen3 model via OpenRouter with 32B parameters. Apache 2.0 licensed, offering strong performance with efficient resource usage and multilingual support.

Alibaba's efficient Qwen3 model via OpenRouter with 14B parameters. Apache 2.0 licensed, optimized for speed and cost-effectiveness while maintaining quality across multiple languages.

xAI's Grok 3 model available via OpenRouter. Beta version of xAI's latest language model with enhanced capabilities.

Google's fast, efficient Gemini 2.0 model via OpenRouter. Optimized for responsive multimodal tasks with strong performance. Scheduled for retirement March 31, 2026.

Small reasoning model optimized for science, math, and coding tasks via OpenRouter. Offers efficient complex reasoning at lower computational cost.

Perplexity AI's Sonar model via OpenRouter with native web search integration. Provides real-time information by searching the web and synthesizing current results into responses.

LiquidAI's lightweight thinking model via OpenRouter. Compact 1.2B parameter model optimized for edge devices and resource-constrained environments. Excels at agentic tasks, data extraction, and RAG applications. Free tier available.

Alibaba's Qwen3 VL multimodal model via OpenRouter. Supports text, images, and video inputs with 262K context window. Features strong visual tool use capabilities and agentic interaction for complex multimodal tasks.

OpenAI reasoning model trained with reinforcement learning via OpenRouter. Designed to think deeply before responding on complex reasoning tasks.

Meta's open-source Llama 3.3 model (70B parameters) via OpenRouter. Instruction-tuned for helpful, high-quality responses.

OpenRouter's intelligent free model router via OpenRouter. Dynamically selects from available free models and smartly filters for required features like image understanding, tool calling, and structured outputs. Perfect for cost-conscious applications.

StepFun's Step 3.5 Flash free model via OpenRouter. 196B sparse MoE with 11B active parameters optimized for reasoning tasks. Features excellent speed and efficiency across long contexts. Free tier available.

Arcee AI's Trinity Large free model via OpenRouter. 400B-parameter sparse MoE excelling in creative writing and agentic navigation. Suitable for real-world applications with free tier access.

Relace's agentic search model via OpenRouter. Specialized for multi-step codebase exploration with parallel tool usage. Claims 4x faster performance than frontier models for code search tasks.

Fast and efficient model from Anthropic's Claude 3.5 series via OpenRouter. Designed for quick, straightforward tasks.

MoonshotAI's Kimi K2 with thinking mode via OpenRouter. Trillion-parameter MoE with 32B active parameters supporting persistent multi-turn reasoning. Capable of 200-300+ tool calls with step-by-step thought process.

Perplexity AI's Sonar Pro with advanced search capabilities via OpenRouter. Features autonomous multi-step reasoning for planning and executing entire research workflows. Combines web search with deep reasoning for complex research tasks.

Anthropic model that raises the industry bar for intelligence, available via OpenRouter. Outperforms competitor models with the speed and cost of mid-tier models.

Cohere's premium enterprise model via OpenRouter. Optimized for retrieval-augmented generation (RAG), document processing, and business applications with exceptional instruction-following.

Cohere's balanced enterprise model via OpenRouter. Provides strong performance for RAG and document tasks with efficient resource usage and reliable instruction-following.

OpenAI's versatile, high-intelligence flagship model via OpenRouter. Accepts text and image inputs with balanced performance across diverse tasks.

Meta's largest open-source Llama 3.1 model via OpenRouter with 405B parameters. Delivers frontier-level performance with instruction tuning for complex reasoning and generation tasks.

Meta's high-performance Llama 3.1 model via OpenRouter with 70B parameters. Balances quality and efficiency with instruction tuning for diverse applications.

Meta's ultra-efficient Llama 3.1 model via OpenRouter with 8B parameters. Optimized for ultra-fast inference and minimal costs while maintaining reliable performance.

Mistral AI's efficient smaller model via OpenRouter. Provides fast inference and lower costs while maintaining good performance for everyday tasks.

Mistral AI's ultra-efficient 7B parameter model via OpenRouter. Optimized for speed and cost-effectiveness while delivering reliable performance for straightforward tasks.

Mistral AI's mixture-of-experts model via OpenRouter with 8 experts and 22B parameters each. Delivers excellent quality across diverse tasks with efficient parameter usage.

Mistral AI's flagship model via OpenRouter. Delivers strong performance across reasoning, coding, and multilingual tasks. Provides a compelling European alternative to frontier models.

Perplexity AI's reasoning-enhanced Sonar model via OpenRouter. Combines deep reasoning capabilities with web search integration for complex research and analysis tasks.