MiniMax M2.5
MiniMax-M2.5Compare MiniMax-M2.5 API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 204.8K
- Maximum input window
- Max output
- 128K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
| Input/ 1M tokens | Output/ 1M tokens | Cache Read/ 1M tokens | Cache Write (5m)/ 1M tokens | Cache Write (1h)/ 1M tokens |
|---|---|---|---|---|
$0.255 | $1.02 | $0.0255 | $0.31875 | $0.51 |
- Input/ 1M tokens
- $0.255
$0.3 - Output/ 1M tokens
- $1.02
$1.2 - Cache Read/ 1M tokens
- $0.0255
$0.03 - Cache Write (5m)/ 1M tokens
- $0.31875
$0.375 - Cache Write (1h)/ 1M tokens
- $0.51
$0.6
| Input/ 1M tokens | Output/ 1M tokens | Cache Read/ 1M tokens | Cache Write (5m)/ 1M tokens | Cache Write (1h)/ 1M tokens |
|---|---|---|---|---|
$0.3 | $1.2 | $0.03 | $0.375 | $0.6 |
- Input/ 1M tokens
- $0.3
- Output/ 1M tokens
- $1.2
- Cache Read/ 1M tokens
- $0.03
- Cache Write (5m)/ 1M tokens
- $0.375
- Cache Write (1h)/ 1M tokens
- $0.6
Capabilities / Supported modalities
Provider & data privacy
ABAB tokenizerPerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·MiniMax M2.5
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 MiniMax M2.5
先规划工作，再推进交付
MiniMax-M2.5 适合需要多步骤完成的编程和办公任务。它可以先梳理需求、功能结构与实现顺序，再参与编码、搜索、测试和结果整理。对于开发团队，它适合从功能设计到迭代审查的连续工作；对于办公助手，它可以围绕一份报告或分析目标安排资料处理。
编程能力覆盖多种语言和全栈工作，包括服务端接口、业务逻辑、数据库以及 Web 或移动端项目。提供现有项目约定、接口行为与验收条件，可以让它把建议落实到实际系统，而不只是做一个界面演示。修改之后，应通过测试与运行反馈继续检查结果。
它以文字输入和输出工作，可阅读源码、日志和文档，并通过工具与外部环境交互。检索任务可以要求它先确定需要回答的问题，再搜索与深入阅读材料，最后整理证据。办公任务可以要求它先规划报告结构、表格计算或幻灯片内容，再由相应工具生成文件并检查效果。
接入 Word、演示文稿或电子表格的编辑工具后，模型可以参与制作与修订文件；单独调用模型时，返回的是文字、代码或结构化内容。把工具能力、业务规则和交付标准一起提供，能够让工作流程更完整。
实际应用问题
适合从零开发功能吗？ 可以先生成需求与架构计划，再分模块实现，并验证接口、数据和交互。
怎样判断办公任务完成？ 检查真实文件是否生成、公式与内容是否正确，以及最终版式是否可用。
Use cases and prompting
从交付物倒推工作步骤
说明最终要拿到什么，以及可使用的工具和材料。
基于这份门店运营数据，制作月度经营报告。
先核对时间范围、指标口径和缺失数据，再列报告提纲。
用表格工具计算客单价与退款率，生成图表；最后整理成管理层可阅读的文档。
每个结论关联计算结果，检查公式与图表范围，并报告完成的文件和未解决的问题。
开发任务可要求先规划功能和依赖，再实现并运行测试。检索任务明确日期、地区与证据要求；工具执行失败时保留返回信息，不把计划步骤写成已完成结果。
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 |
|---|---|---|---|
| Alibaba | Unlimited | Unlimited | Unlimited |
| official | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about MiniMax-M2.5
What is MiniMax-M2.5?
Compare MiniMax-M2.5 API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call MiniMax-M2.5?
Create an API key with access to MiniMax-M2.5, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is MiniMax-M2.5 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 MiniMax-M2.5?
The model catalog lists a context window of 204800 tokens. Check the selected endpoint for request limits.
What is the maximum output of MiniMax-M2.5?
The model catalog lists a maximum output of 128000 tokens. Your request settings may set a lower limit.
How should I evaluate MiniMax-M2.5 for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.