Claude Opus 5.5
Anthropic
Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
- Anthropic
- Vision
- Tool calling
AI model category
The workhorses: writing, summarizing, answering questions, extracting data and calling tools.
General purpose models cover most business AI work: drafting replies, summarizing documents, extracting fields, classifying requests and calling tools on behalf of a user. The differences between them are in speed, price, context size and how reliably they follow instructions and formats.
Many providers offer the same family in several sizes. The smaller sizes are often good enough for high-volume, simple tasks and cost a fraction of the flagship.
General purpose
Anthropic
Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
Anthropic
Anthropic's balance of speed and intelligence: a strong everyday model for assistants, document work, tool calling and coding.
Anthropic
Anthropic's fastest and lowest-cost Claude model, with near-frontier intelligence for high-volume and real-time work.
Google's most capable Flash model, stable since September 2026, for agents, software engineering and enterprise workflows with full multimodal input.
Google's lowest-cost current Gemini model for high-throughput work such as sub-agent tasks and document parsing.
Google's open-weight model family under Apache 2.0, in sizes from phone-friendly to 31B, with image input and function calling.
Meta
An open-weight Llama 4 model with image input and a very long context window, for teams that want to host a capable model themselves.
Meta
The larger Llama 4 open-weight model, with image input and a 1 million token context window, for self-hosted assistants and analysis.
Meta
An older, text-only open-weight Llama model with tool use and a 128K token window, still widely hosted and well understood.
Meta
Meta's newer proprietary model family, offered through the Meta Model API, with text, image, video and PDF input, tool calling and a 1 million token window.
Mistral AI
Mistral's open-weight general-purpose flagship under Apache 2.0, with image input, tool calling, structured outputs and a 256K token window.
Mistral AI
Mistral's efficient open-weight model under Apache 2.0, one hybrid model for instructions, reasoning and coding, with tool calling and a 256K window.
Mistral AI
A newer open-weight Mistral model for agent and coding work, with image input, tool calling, structured outputs and a 256K window.
OpenAI
The middle model of the GPT-6 family, positioned for complex coding and agentic workflows at a mid price level.
OpenAI
OpenAI's most efficient model for focused, high-volume tasks, with vision, tool calling and structured outputs at the lowest price level in the family.
OpenAI
An older OpenAI model described as its smartest non-reasoning model, strong at following instructions and calling tools, with a very long context window.
OpenAI
A compact, low-cost older OpenAI model for focused tasks, with vision, tool calling and structured outputs and a 128K token window.
DeepSeek
DeepSeek's default, best-value model: open weights under MIT, image input, tool calling, JSON output, optional thinking and a 1 million token window.
Alibaba Cloud
Alibaba's current Qwen flagship for long autonomous coding and professional work, with image and video input, tool calling, JSON Schema output and a 1 million token window.
xAI
xAI's current flagship for coding, agent tasks and knowledge work, with image input, tool calling, structured outputs, reasoning effort levels and a 500K window.
Cohere
Cohere's enterprise flagship for multimodal, multilingual agent tasks, with 48 languages, tool calling, JSON output and open weights under Apache 2.0.
How to choose
Pick two or three candidates from different providers and test them on the same set of real examples. Measure accuracy, format errors, speed and cost per thousand requests. Then consider data policy, region and whether you may want to switch providers later.
For high volume, try the smallest model first and move up only where quality falls short.
Other categories
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