Claude Opus 5

Claude Opus 5 by Anthropic: $5 per 1M input and $25 per 1M output tokens, 1M context. Call it with one OpenAI-compatible API key, compare it with similar models, start free.

ReasoningReads imagesTool callingJSON schemaStreamingWeb searchPrompt cachingBatch

Claude Opus 5 is served by Anthropic and called through odnoga on /v1/chat/completions, in the same OpenAI-compatible shape every other model on that endpoint uses. It is a reasoning model, so it spends extra output tokens working through a problem before answering — budget for higher output cost on hard tasks. It accepts images alongside text. It supports tool and function calling. It can be forced to return structured JSON. Its 1M-token context window sets how much input you can send in one request. Cached input is billed at $0.5 per 1M tokens, so repeated prefixes cost less.

Specification and price

VendorAnthropic
Model IDclaude-opus-5
Context window1M tokens
Max output128K tokens
Served on/v1/chat/completions
CapabilitiesReasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch
Your plan
Per 1M tokensVendor costYour price on Free+7%
Input$5$5.38
Output$25$26.88
Cached input$0.5$0.538

Vendor cost is the list price per million tokens as recorded in the odnoga catalog; your price applies your plan margin with the same formula that bills every request — see pricing. Pricing

Call it through odnoga

const res = await fetch("https://api.odnoga.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.ODNOGA_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "claude-opus-5",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

One endpoint, one key, one bill — /v1/chat/completions takes the same shape whichever vendor is behind it. Swap the model id and odnoga handles keys, routing, limits and cost accounting.

What Claude Opus 5 can do

Everything below is what the model itself supports. Ask for something it does not do and odnoga tells you before the request reaches the provider, instead of returning a worse answer.

Reasoning

Works through a problem step by step before answering, which costs more tokens and buys accuracy on hard tasks.

Reads images

Send a screenshot, a photo or a scan in the same message as your text.

Tool calling

The model can call functions you define and use what they return.

JSON mode

Answers with valid JSON instead of prose you would have to parse.

JSON schema

Answers in the exact shape you specify, so the response fits your types without a fallback path.

Streaming

Tokens arrive as they are produced, so your interface can answer immediately.

Web search

Can look something up rather than answer from training data alone. Billed per search.

Prompt caching

A prompt you send repeatedly is charged at the cached rate, which is a fraction of the input price.

Batch

Work that can wait goes through at a lower price.

Beyond text

Reads PDFs

Send a document and ask about it, without extracting the text yourself first.

Finer control

  • Structured outputs · The provider guarantees the schema rather than merely aiming for it.
  • Parallel tools · Can call several of your functions in one turn instead of one after another.

How to use Claude Opus 5

Reviewed 2026-09-14

Best for

  • Complex agentic coding and enterprise knowledge work — the use Anthropic states for this model.
  • Long-horizon tasks: multi-hour agent runs, migrations, large refactors, deep document review.
  • Work over very large inputs, with a 1M-token context window and 128K max output.
  • Careful drafting where quality of the written answer matters more than price per call.

Not the right pick when

  • High-volume, simple calls — Claude Haiku 4.5 or a nano-tier model costs a fraction.
  • Latency-critical interactive UI, since thinking is on by default on this generation.
  • Tasks where Claude Sonnet 5 already passes your evaluation: same family, materially lower price.

Practical tips through odnoga

  1. 01Thinking is on by default in this generation and disabling it is restricted — plan for the extra output tokens instead of trying to switch them off.
  2. 02Structure the prompt so the long, stable part comes first; prompt caching then cuts the cost of repeated context sharply.
  3. 03Give agents explicit stop conditions; long-horizon capability means long-horizon spend if the loop has no exit.
  4. 04Compare Opus 5 against Sonnet 5 on the same frozen test cases before making it the default — the gap is task-specific.

What a month costs

1,000 calls a month, 10,000 input tokens and 2,000 output tokens each, at your Free price (vendor cost +7%):

Input (10M tokens)$53.76
Output (2M tokens)$53.76
Your cost per month on Free$108

Vendor list cost $100 + odnoga margin $7.53 (+7%). Cached input or answer reuse lowers it; odnoga records both numbers per request.

If Claude Opus 5 is not the one

Models that take the same kind of input, are priced the same way, and do the closest thing to what this one does. Not a quality ranking — odnoga does not benchmark models.

ModelContextInput / 1MOutput / 1MCapabilities
Claude Opus 51M$5$25Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch
Claude Opus 4.61M$5$25Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch
Claude Opus 4.71M$5$25Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch
Claude Opus 4.81M$5$25Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch

Questions

What is Claude Opus 5 best at?
Anthropic positions it for complex agentic coding and enterprise work, describing gains over Opus 4.8 in deep reasoning, agentic and long-horizon tasks.
Opus 5 or Sonnet 5?
Sonnet 5 is the speed-and-intelligence balance point; Opus 5 is the heavier option for the hardest work. Run both on your own test cases in the odnoga evaluation laboratory and compare pass rate against cost before choosing.
Why is my output token count higher than expected?
Thinking is enabled by default on this generation, and thinking tokens are billed as output. odnoga shows the real token split per request so the increase is visible rather than a surprise on the invoice.

All models · Pricing · Docs · Compare models in the evaluation lab

Sources: Anthropic — Claude Opus 5 overview, Anthropic — what is new in Claude Opus 5

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