Kimi K2.7 Code
kimi-k2.7-codeCompare kimi-k2.7-code API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 262.1K
- Maximum input window
- Max output
- 235.9K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
| Input/ 1M tokens | Output/ 1M tokens | Cache Read/ 1M tokens |
|---|---|---|
$0.95 | $4 | $0.19 |
- Input/ 1M tokens
- $0.95
- Output/ 1M tokens
- $4
- Cache Read/ 1M tokens
- $0.19
| Input/ 1M tokens | Output/ 1M tokens | Cache Read/ 1M tokens |
|---|---|---|
$0.95 | $4 | $0.19 |
- Input/ 1M tokens
- $0.95
- Output/ 1M tokens
- $4
- Cache Read/ 1M tokens
- $0.19
Capabilities / Supported modalities
Provider & data privacy
Kimi tokenizerPerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Kimi K2.7 Code
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 Kimi K2.7 Code
围绕完整开发任务协作
Kimi K2.7 Code 是面向编程的智能体模型，重点在较长流程的软件工程任务。它适合处理需要读懂项目、修改多个文件并反复检查的需求，例如新增接口、修复复杂故障、调整模块边界或完善已有功能。
一次完整开发通常要经过理解、实现和验证。可以先让模型读取目标模块及其调用关系，说明准备修改哪些位置，再实施必要改动。在应用提供文件和终端工具时，它可以根据编译、测试或运行结果继续修正，直到达到明确的交付条件。
对于已有项目，应把技术栈、代码习惯、接口兼容要求和禁止修改的范围写清楚。功能任务最好提供具体的前后行为；故障任务则附错误日志、复现输入和预期结果。它也具备视觉输入基础，页面相关工作可以辅以截图，但实际实现仍需要结合代码结构和运行环境判断。
K2.7 Code 的设计关注完整任务完成与推理效率。使用时无需靠长篇指令重复强调“认真思考”，更有用的是提供可验证目标和真实反馈。长任务结束前，让它汇总改动、实际运行的检查与剩余问题，方便评审和接续；提出了测试方法，并不等于已经运行通过。
Use cases and prompting
跨文件修复提示词
“请修复上传完成后偶尔显示旧状态的问题。下面提供前端状态管理、接口实现和复现步骤。先追踪状态更新路径，找出能解释现象的原因，再做最小改动。执行相关检查后说明修复前后的行为，并列出未覆盖的边界情况。”
常见问题
- 怎样减少无关重构？明确允许修改的模块，要求每项改动说明与目标问题的关系。
- 测试失败后如何继续？把完整失败结果返回给模型，让它判断是环境、测试假设还是实现的问题。
- 长开发任务怎样交接？保留文件变更、关键决定、检查结果和待办清单，让下一轮从实际状态继续。
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 |
|---|---|---|---|
| Moonshot | Unlimited | Unlimited | Unlimited |
| official | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about kimi-k2.7-code
What is kimi-k2.7-code?
Compare kimi-k2.7-code API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call kimi-k2.7-code?
Create an API key with access to kimi-k2.7-code, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is kimi-k2.7-code 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 kimi-k2.7-code?
The model catalog lists a context window of 262144 tokens. Check the selected endpoint for request limits.
What is the maximum output of kimi-k2.7-code?
The model catalog lists a maximum output of 235929 tokens. Your request settings may set a lower limit.
How should I evaluate kimi-k2.7-code for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.