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Claude Opus 4.7 API — Anthropic's Flagship Reasoning Model

Claude Opus 4.7 is Anthropic's flagship model for premium coding, agent workflows, and long-context analysis — 1M context, 128K max output, vision input, prompt caching, and standard /v1/chat/completions in one call. Pay-as-you-go pricing in USD.

Highlights
Opus-class reasoning · temperature & top_p control
Best for
Code review, analysis, long documents
Input
Chat messages (OpenAI-compatible)
Output
Text, streaming optional
Claude Opus 4.7modelclaude-opus-4-7

Claude Opus 4.7 playground

Chat models run on the api.reapi.ai gateway, which has its own console and its own key. Open the console to run Claude Opus 4.7 through the OpenAI-compatible Chat Completions surface.

Open consoleToken rates

What is the Claude Opus 4.7 API?

Claude Opus 4.7 is Anthropic's flagship reasoning model, aimed at premium coding, agent workflows, and long-context analysis. It runs on an OpenAI-compatible /v1/chat/completions endpoint (the native /v1/messages surface is available too) with a 1M-token context window, up to 128K output tokens per call, vision input, prompt caching, tool use, and the familiar temperature and top_p controls. Usage is billed per million tokens, with input and output priced separately.

What you can build with this model

Real-world workflows and production use cases you can build and ship with this model.

Claude Opus 4.7 refactoring a large codebase in one pass

High-stakes coding and large refactors

Claude Opus 4.7 is the right model for architecture work, multi-file refactors, code review, migration planning, and long-form engineering deliverables that need fewer follow-up passes. Output quality dominates raw speed — pick it when the call has real downstream cost if it goes wrong.

Read the API docs
Claude Opus 4.7 driving a multi-step agent with tool use

Agent workflows and tool orchestration

Claude Opus 4.7 holds task state across long agent runs, plans multi-step actions reliably, and uses tools without drifting off-spec. The right default when lighter models start dropping constraints or losing context mid-workflow.

Claude Opus 4.7 reasoning across a 1M-token analysis pack

Large-context analysis and review

Feed entire codebases, long research packs, multi-file technical material, or full policy documents into a single Claude Opus 4.7 request. The 1M token context window means analysis-heavy workflows rarely need chunking — the model sees the whole input and returns a coherent answer.

Pricing

Credit-based — 1 credit = $0.001 USD. Pay only for completed generations.

First test cost
$22,000 credits

One sample at the cheapest tier (1M tokens).

Testing budget guide
Add credits
$10
≈ 5 tests
$50
≈ 25 tests
$100
≈ 50 tests
ModelCategoryPrice
TokensInput tokens
$2
1M tokens
Output tokens
$10
1M tokens

Why reAPI

Drop-in access for a flagship Claude model

The Claude Opus 4.7 API speaks OpenAI Chat Completions verbatim. Moving an existing OpenAI integration to a premium Claude route is a base URL, an API key, and a model-string change — not a platform rewrite. The same `messages` array, the same streaming format, and the native Anthropic /v1/messages surface is available too for SDK callers that prefer it.

Premium reasoning where it matters

Claude Opus 4.7 is Anthropic's flagship — best output quality on hard coding, complex agent planning, and long-context analysis. Route premium workloads here when the per-call cost is justified by the answer quality; send simpler traffic to cheaper Claude or GPT models on the same key.

One key across GPT, Claude, and Gemini

A single api.reapi.ai key unlocks Claude Opus 4.7 alongside GPT-5.5, Gemini 3.1 Pro, and every other frontier chat model on the platform. Compare vendors, add fallbacks, and route traffic per call with a configuration change instead of an integration project.

Ship the Claude Opus 4.7 API in three steps

  1. step 01

    Create an account and key on api.reapi.ai

    Sign up at api.reapi.ai, open the console, generate an API key under API Keys, and top up tokens under Top Up. The chat workspace is separate from the reapi.ai image/video gateway — keys do not cross over.

    Open
  2. step 02

    Send your first request

    POST https://api.reapi.ai/v1/chat/completions with `model: "claude-opus-4-7"`, your `messages` array, and `max_tokens` set generously. The endpoint uses the standard chat-completions format, including streamed responses; the native Anthropic /v1/messages format works too.

    Open
  3. step 03

    Tune for cost and stability

    Use prompt caching for stable system prompts and recurring long inputs to bring repeated-context costs down. Reserve Claude Opus 4.7 for the highest-value calls and route everything else to a cheaper model on the same key.

    Open
docs/api/claude-opus-4-7

API reference

Drop-in code and the full parameter table.

View full reference
curl https://api.reapi.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "group": "default",
    "messages": [
      { "role": "user", "content": "Hello" }
    ],
    "stream": true,
    "max_tokens": 4096,
    "temperature": 0.7
  }'

Parameter validation failed

Rejected synchronously with the failing field named. Check enum values, ranges, and URL fields — nothing is charged.

Authentication or balance issue

401 means a missing or invalid Bearer key; 402 means the reserve exceeds your balance. Manage keys and credits in the console.

Content or material rejected

Reference material and outputs pass automated moderation. Rejected tasks fail with a clear error and a full refund.

Task failed or timed out

A task that reaches a failed state is never charged — the reserve refunds automatically. Keep the task id and retry when ready.

Frequently asked questions

Common questions about this model.

Claude Opus 4.7 is billed pay-as-you-go in USD against your api.reapi.ai token balance — see the pricing card on this page for the live per-1M-token rate. Prompt-caching rates (cache read and cache write) are listed in the same card; cache hits are dramatically cheaper than re-sending the same tokens. Failed requests are not charged.

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