MiMo V2.5 Pro
mimo-v2.5-proCompare mimo-v2.5-pro API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 1.1M
- Maximum input window
- Max output
- 131.1K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
| Input/ 1M tokens | Output/ 1M tokens | Cache Read/ 1M tokens |
|---|---|---|
$0.435 | $0.87 | $0.0036 |
- Input/ 1M tokens
- $0.435
- Output/ 1M tokens
- $0.87
- Cache Read/ 1M tokens
- $0.0036
Capabilities / Supported modalities
Provider & data privacy
BPE (vendor-specific)Performance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·MiMo V2.5 Pro
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
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 MiMo V2.5 Pro
在长项目背景中追踪关键关系
MiMo-V2.5-Pro 面向要求较高的推理、软件工程和持续执行任务。它接收与输出文本，适合同时阅读大量代码、接口文档和历史讨论，再梳理其中的依赖关系，帮助团队推进跨模块修改或复杂问题调查。
处理大型项目时，重要信息常分散在不同位置：一个接口的约定写在文档里，实际调用藏在多个模块中，历史决定又出现在讨论记录中。可以让模型先建立依赖与约束清单，再判断哪些改动会影响其他环节。较长上下文有助于将这些背景保留在同一任务中，但仍应指明需要解决的具体问题。
它的设计强调长流程工具协作、指令遵循与任务连贯性。在具备项目工具的应用中，可以安排它读取文件、实施修改、运行检查，并根据结果继续推进。复杂任务最好按依赖顺序完成，每个阶段写清输入、产出和通过条件，让长时间工作有明确进度。
使用时应把项目规范、兼容要求和禁止修改的内容放在清楚的位置。遇到信息冲突，让模型列出不同记录及其适用范围，再决定需要怎样验证。最终交付应说明实际修改、已执行检查和剩余限制，让长篇分析能够落到可检查的工程结果。
Use cases and prompting
依赖分析提示词
“请根据这些接口文档、调用代码和历史设计记录，评估把用户标识改为字符串的影响。先建立依赖图的文字清单，按数据存储、服务接口和客户端列出受影响位置，再给出兼容迁移顺序。对每一步说明验证方法及未确认的前提。”
常见问题
- 材料很多，怎样突出关键约束？先提供目标与约束清单，为文档和代码标注名称，再说明重点关注的依赖。
- 能直接读图片和视频吗？这个模型主要处理文本，可先提取相关文字或结构说明再交给它分析。
- 多轮工具调用后怎样保持进度？保留阶段结果、工具反馈和待验证事项，要求下一步解释其依据。
API access
API documentation
Code samples
/v1/chat/completions| 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 |
|---|---|---|---|
| XiaomiMIMO | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about mimo-v2.5-pro
What is mimo-v2.5-pro?
Compare mimo-v2.5-pro API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call mimo-v2.5-pro?
Create an API key with access to mimo-v2.5-pro, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is mimo-v2.5-pro 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 mimo-v2.5-pro?
The model catalog lists a context window of 1050000 tokens. Check the selected endpoint for request limits.
What is the maximum output of mimo-v2.5-pro?
The model catalog lists a maximum output of 131072 tokens. Your request settings may set a lower limit.
How should I evaluate mimo-v2.5-pro for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.