Claude Opus 5
claude-opus-5Compare claude-opus-5 API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 1M
- Maximum input window
- Max output
- 128K
- Maximum tokens per response
- Modalities
- →
- Knowledge cutoff
- May 2026
- Released
- Jul 2026
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
Anthropic Claude tokenizerPerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Claude Opus 5
Intelligence Index
Claude Opus 5
50.8
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About Claude Opus 5
为复杂任务保留完整背景
Claude Opus 5 是 Anthropic 面向高难度推理、编程和较长工作流程的模型。它能理解文本与图片，适合阅读代码、审查改动、分析图表和文档，也可以协助形成内容完整的专业交付物。
代码审查是很实用的场景。把改动、相关调用位置和业务要求一起提供，可以让它检查行为变化、异常路径和潜在漏洞，再按影响程度说明问题。对于跨文件任务，可以要求它先追踪依赖，再判断某项修改是否真正解决原因，避免只关注局部语法或风格。
在知识工作中，它可以结合长文档与视觉材料梳理证据，比较多个方案，并把结论整理成报告、分析框架或办公材料。复杂图表和页面截图可直接作为分析输入；如果需要精确数字计算，提供原始数据和计算工具，会比仅凭图像估读更稳妥。
模型支持自适应思考和工具调用。任务边界明确时，可以尝试较低的推理投入；需要深入判断或跨材料综合时，再增加投入。应用具备子任务调度能力时，也可以让它分配相互独立的调查工作，最终合并结论。交付前应要求它清楚区分已验证结果、推断和仍缺失的证据，让复杂任务的完成状态容易判断。
Use cases and prompting
代码审查提示词
“请审查这次结算模块改动。结合差异和调用代码，重点检查重复请求、失败重试、边界金额和状态回滚。只报告能说明触发条件与影响的问题，按严重程度排序；每项附相关代码位置、复现思路和建议修复。没有发现的风险不要凑数。”
常见问题
- 审查结论太泛怎么办？要求每个问题给出具体触发输入、实际行为和预期行为，并提供关联代码。
- 可以看图表和截图吗？可以，复杂图表最好附图例与数据口径；关键数值可补充原始表格。
- 怎样安排并行子任务？在支持调度的应用中按模块或证据来源拆分，并由主任务核对冲突和汇总结果。
API access
API documentation
Code samples
/v1/messages| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| CCMax-ZL | Unlimited | Unlimited | Unlimited |
| Claude kiro | Unlimited | Unlimited | Unlimited |
| Claude kiro ZL | Unlimited | Unlimited | Unlimited |
| claude特供 | Unlimited | Unlimited | Unlimited |
| default | Unlimited | Unlimited | Unlimited |
| Vertex Claude | Unlimited | Unlimited | Unlimited |
| AmazonBedrock | Unlimited | Unlimited | Unlimited |
| AmazonBedrock-ZL | Unlimited | Unlimited | Unlimited |
| CCMax | Unlimited | Unlimited | Unlimited |
| Anthropic | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about claude-opus-5
What is claude-opus-5?
Compare claude-opus-5 API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call claude-opus-5?
Create an API key with access to claude-opus-5, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is claude-opus-5 priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of claude-opus-5?
The model catalog lists a context window of 1000000 tokens. Check the selected endpoint for request limits.
What is the maximum output of claude-opus-5?
The model catalog lists a maximum output of 128000 tokens. Your request settings may set a lower limit.
How should I evaluate claude-opus-5 for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.