How much does prompt caching save on claude-opus-4-5-20251101?

claude-opus-4-5-20251101 supports prompt caching, which can significantly reduce costs for repeated prompts with shared prefixes. The cache read price is substantially lower than the standard input price. Check the current pricing page for the exact cache hit discount ratio for claude-opus-4-5-20251101.

How should you set the output budget for claude-opus-4-5-20251101?

For claude-opus-4-5-20251101, set the max_tokens or max_completion_tokens parameter to control spending per call. Start with a budget aligned to your typical response length and increase only when longer outputs are genuinely needed. Monitor token usage in the API response headers to tune your budget over time.

When was Claude Opus 4.5 released, and is it still maintained?

Claude Opus 4.5 was released on 2025-11-24. Its catalog status is stable. Check the model page for deprecation notices before you build a long-lived integration on it.

What is the max output length for claude-opus-4-5-20251101?

claude-opus-4-5-20251101 supports up to 64000 output tokens per request. Plan your prompts to stay within this limit, and use the max_tokens or max_completion_tokens parameter to control output length.

Does claude-opus-4-5-20251101 have a free tier?

Claude Opus 4.5 is billed per use and the record publishes no free-tier allowance. The current published rates are input $5.0000 per 1M tokens and output $25.0000 per 1M tokens. Trial credit or promotional quota is tied to your account rather than to the model, so check the console before planning around a free tier.

Model detail

Claude Opus 4.5 20251101

Q: Does Claude Opus 4.5 support tool calling and structured output?

Yes. Opus 4.5 supports advanced tool use, extended context management, and coordinated multi-agent setups. Test with your specific tool definitions.

Provided by Anthropic

Pay-as-you-go

Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and reasoning benchmarks, and improved robustness to prompt injection. The model is designed to operate efficiently across varied effort levels, enabling developers to trade off speed, depth, and token usage depending on task requirements. It comes with a new parameter to control token efficiency, which can be accessed using the OpenRouter Verbosity parameter with low, medium, or high. Opus 4.5 supports advanced tool use, extended context management, and coordinated multi-agent setups, making it well-suited for autonomous research, debugging, multi-step planning, and spreadsheet/browser manipulation. It delivers substantial gains in structured reasoning, execution reliability, and alignment compared to prior Opus generations, while reducing token overhead and improving performance on long-running tasks.

Model specs

Model ID: claude-opus-4-5-20251101

Context length: 200K
Max output: 64K
I/O modalities
Released: 2025-11

API endpoints

One MixRoute gateway, OpenAI-compatible

Anthropic Messages /v1/messages POST
OpenAI-compatible /v1/chat/completions POST
Gemini /v1beta/models/{model}:generateContent POST

Pricing

Flat rate, unit: /1M Tokens

Input

$5.0000 /1M Tokens

Completion

$25.0000 /1M Tokens

Cache read

$0.5000 /1M Tokens

Cache creation

$6.2500 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Complex software engineering and multi-agent setups

Use Claude Opus 4.5 for autonomous research, debugging, multi-step planning, and spreadsheet/browser manipulation. It supports advanced tool use, extended context management, and coordinated multi-agent setups.

What should you check before using it?

Tune token efficiency and tool orchestration

Opus 4.5 supports a verbosity parameter (low/medium/high) to control token efficiency. Test your multi-agent setups and verify the improved prompt injection robustness. Knowledge cutoff: 2025-05.

Why use it through MixRoute?

Claude Opus 4.5 cache reads cut repeated-prompt cost

Cached prefixes are billed at 0.50 USD per 1M tokens instead of 5 USD, so repeated system prompts cost less. MixRoute serves Claude Opus 4.5 on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID claude-opus-4-5-20251101 and re-run your integration tests.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

Claude Opus 4.5 supports function and tool calls.

EX Send a tools definition; the response returns tool_calls to execute and feed results back.

Structured output

Claude Opus 4.5 can produce JSON-formatted output on demand.

EX response_format: { type: "json_schema" } forces valid JSON output.

Streaming

Claude Opus 4.5 supports streamed responses.

EX stream: true streams tokens incrementally, so chat UIs render as they arrive.

Prompt caching

Claude Opus 4.5 supports prompt caching under supported routing conditions.

EX Keep the system prompt and tool definitions at the start of the request; repeated prefixes are automatically billed at the cache-read rate.

Vision input

Claude Opus 4.5 can process image inputs alongside text.

EX Pass a base64-encoded image in a image_url content part alongside text messages.

OpenAI SDK

Call Claude Opus 4.5 through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 200K

Output tokens Max per request 64K

Requests / month

Cache hit rate 0%

Share of the same prefix read repeatedly, up to 100%

FAQ

Compare claude-opus-4-5-20251101 against models of similar capability and pricing on your actual workload. Evaluate latency, output quality, instruction following, and cost per task. Run side-by-side tests with your own prompts — the best model depends on your specific use case, not just benchmark scores.

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

claude-opus-4-5-20251101

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs