MiMo V2.6 Pro
mimo-v2.6-proCompare mimo-v2.6-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
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 V2.6 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 V2.6 Pro
把看到、听到的信息用于实际任务
MiMo-V2.6-Pro 是小米MiMo系列的多模态模型，能够结合文本、图片、视频和音频进行分析，输出文字结果。它适合需要跨素材理解问题的项目，例如根据产品演示与口头需求规划实现，结合代码和界面状态排障，或把多轮讨论整理成可执行的工作方案。
面向长流程与工具协作
模型关注编程、通用智能体与视觉任务，可以围绕较长的代码、工具记录和项目上下文持续工作。接入工具后，应用可以让它读取文件、执行验证或观察界面，并把结果交回继续分析。任务是否完成应由实际产物与检查结果判断，不能只看模型是否写出了完整计划。
多模态素材最好有清楚分工：文字说明目标与约束，录像展示操作过程，截图补充细节，音频保留用户原意。对同一个问题，将这些证据放在一起比单独摘要更有价值，也更容易发现描述与实际行为之间的差异。
让复杂工作有接续点
可以按理解需求、实施方案、验证结果和整理交付推进。每阶段保存关键决策、已经完成的内容及未解决问题，后续修改沿用这些结果。对于不清晰的画面和含糊的口头要求，应提出待确认项；复杂动作或界面状态要通过新观察验证，避免把一次推断沿用到整个流程。
Use cases and prompting
从演示到实现的示例
“结合原型演示视频、需求讨论音频和当前代码，整理待开发功能。先区分已实现、只在演示中出现和仍有歧义的部分，再按依赖顺序提出最小实现计划。每阶段说明验收步骤，保留原有登录与权限逻辑。”
提供清晰素材，并说明各文件的角色和时间顺序。
既有录像又有截图，是否重复？
录像适合观察流程和变化，截图适合查看按钮、文字和布局细节；可用清晰截图补充录像里看不清的位置。
如何让长任务跨多轮继续？
保留工具结果和阶段记录，继续时提供已完成事项、剩余目标和最新约束，减少重复分析。
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-v2.6-pro
What is mimo-v2.6-pro?
Compare mimo-v2.6-pro API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call mimo-v2.6-pro?
Create an API key with access to mimo-v2.6-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-v2.6-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-v2.6-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-v2.6-pro?
The model catalog lists a maximum output of 131072 tokens. Your request settings may set a lower limit.
How should I evaluate mimo-v2.6-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.