Claude Opus 5 Fast
Neural Network
Claude Opus 5 Fast is Anthropic's flagship model for complex reasoning, development, and agentic tasks with image analysis.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 000 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- none, low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Claude Opus 5 Fast?
Claude Opus 5 Fast is Anthropic's flagship model for demanding reasoning, development, and long agentic tasks requiring multi-step goal retention. It excels at end-to-end coding: writing and editing projects, conducting reviews, debugging, analyzing failure causes, and interpreting visual materials like diagrams and screenshots. In BotHub, the model is accessible from Russia without a VPN or foreign card. You pay with Russian cards in rubles only for consumed tokens, which do not expire. Access over 250 neural networks in one window, switch between them, or compare answers instantly. A unified OpenAI-compatible API eliminates the need to rewrite integrations, and requests are protected by AES-GCM encryption. It is perfect for reviewing pull requests, finding regressions before release, refactoring legacy code, migrating to new frameworks, debugging via stack traces, building agents with function calling, and reading interface diagrams. For teams, we offer contracts, invoices, electronic document management, and an admin panel with limits, making it easy to integrate Claude Opus 5 into company workflows.Frequently asked questions about Claude Opus 5 Fast
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
claude-opus-5-fast works with text, images, and documents: it parses codebases, writes and refactors code, finds bugs, analyzes reports and contracts, and solves math and science problems. A 1,000,000 token context allows you to keep an entire project in one conversation without splitting it up.
The model outputs up to 128,000 tokens in a single response. This is enough for a voluminous technical document, a detailed analysis, or a large code file in its entirety, without constant requests to continue. If the task is larger, break it into steps: the million-token context will retain the entire conversation history.
Yes, reasoning before answering is confirmed in the model's capabilities: it unfolds its thought process, checks intermediate steps, and only then formulates a conclusion. This is especially noticeable in logic, calculations, code debugging, and tasks where the sequence of actions is more important than the speed of the reply.
Yes, the model supports function calling and structured JSON output, making it easy to integrate into agents, pipelines, and backend logic. In BotHub, it is available via a unified OpenAI-compatible API, so you can switch to another model without rewriting your integration.
Images and documents, yes: screenshots, diagrams, charts, and files can be sent directly to the chat for analysis. Audio and video input is not noted in our data, so for audio tracks, it is more convenient to use a separate model in BotHub designed for speech recognition.
The language of prompts and responses is not described in our data, so we cannot make specific promises—it is easier to test it on your real task. In BotHub, this is simple: pay-as-you-go for tokens, no subscription, tokens do not expire, and access from Russia without a VPN or foreign card.