MoonshotAI: Kimi K2.7 Code
Kimi K2.7 Code is a Moonshot AI model that accepts text and image input and supports tool calling and reasoning. It offers a 262,144-token context window with up to 235,929 completion tokens, enough to take in large codebases or long documents and return lengthy outputs in a single pass. The facts available do not confirm structured output support or whether the weights are open, so teams that depend on either should verify before committing. Shortlist it if coding is the priority and output cost matters. At $0.60 per million input tokens and $3.50 per million output tokens, it is priced in a moderate range, and it posts a top coding index score of 100.0 alongside a blended score of 74.1 across three benchmarks. Its agentic score of 48.8 is notably weaker, so for multi-step autonomous workflows it warrants side-by-side testing against alternatives, and coverage of only three benchmarks leaves its broader standing partly unproven.
Benchmark results
Independent, published benchmarks. Blended score 74.1 across 3 benchmarks, last refreshed 2026-11-08. How scoring works →
| Benchmark | Measures | Score |
|---|---|---|
| AI Index | broad capability composite | 69.2 |
| AI Index Coding | software engineering tasks | 100.0 |
| AI Index Agentic | multi-step tool-using tasks | 48.8 |
- Model ID
- moonshotai/kimi-k2.7-code
- Vendor
- moonshotai
- Released
- June 2026
- Tokenizer
- Other
- Input Modalities
- text, image
- Output Modalities
- text
- Max Output
- 235,929 tokens
- Tool Calling
- ✓ supported
- Structured Output
- ✓ supported
- Reasoning Mode
- ✓ supported
- Vision
- ✓ accepts images
- Audio
- no
- Moderated
- no
What it costs in practice
Computed from the current $0.60/M input and $3.50/M output rates. Run your own numbers →
| Job | Tokens | Cost |
|---|---|---|
| Summarize a 50-page report | 30k in / 1.5k out | $0.02 |
| Classify 1,000 customer emails | 500k in / 50k out | $0.47 |
| A month of a busy support chatbot | 5M in / 2M out | $10.00 |
Price & spec history
Tracked daily by PicksByModel since 2026-07-17.
| Date | Input /M | Output /M | Context |
|---|---|---|---|
| 2026-10-31 | $0.60 | $3.50 | 262,144 |
| 2026-10-27 | $0.56 | $3.10 | 262,144 |
| 2026-09-30 | $0.67 | $3.35 | 262,144 |
| 2026-09-25 | $0.66 | $3.30 | 262,144 |
| 2026-09-23 | $0.71 | $3.30 | 262,144 |
| 2026-09-16 | $0.71 | $3.21 | 262,144 |
| 2026-09-08 | $0.71 | $3.50 | 262,144 |
| 2026-08-28 | $0.66 | $3.40 | 262,144 |
| 2026-08-21 | $0.67 | $3.40 | 262,144 |
| 2026-08-15 | $0.71 | $3.50 | 262,144 |
| 2026-08-13 | $0.67 | $3.40 | 262,144 |
| 2026-08-06 | $0.70 | $3.50 | 262,144 |
| 2026-07-27 | $0.73 | $3.50 | 262,144 |
| 2026-07-26 | $0.75 | $3.50 | 262,144 |
| 2026-07-25 | $0.78 | $3.50 | 262,144 |
| 2026-07-24 | $0.71 | $3.50 | 262,144 |
| 2026-07-21 | $0.82 | $3.75 | 262,144 |
| 2026-07-19 | $0.85 | $3.80 | 262,144 |
| 2026-07-18 | $1.00 | $4.40 | 262,144 |
| 2026-07-17 | $0.75 | $3.50 | 262,144 |
Category rankings
Where MoonshotAI: Kimi K2.7 Code places across the 10 categories it ranks in. How we rank →
| # | Category | Score |
|---|---|---|
| #7 | Image CaptioningVision · of 25 ranked | 121 |
| #9 | JSON ExtractionData · of 25 ranked | 147 |
| #10 | Dataset AnnotationResearch · of 25 ranked | 143 |
| #11 | Bulk Data LabelingData · of 25 ranked | 134 |
| #11 | Short-Form SummarizationWriting · of 25 ranked | 130 |
| #11 | Email DraftingWriting · of 25 ranked | 126 |
| #11 | Language LearningEducation · of 25 ranked | 126 |
| #11 | Chat CompanionPersonal · of 25 ranked | 130 |
| #12 | Customer SupportBusiness · of 25 ranked | 133 |
| #12 | Trivia & General KnowledgePersonal · of 25 ranked | 120 |
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Quick answers
- How much does MoonshotAI: Kimi K2.7 Code cost?
- $0.60 per million input tokens and $3.50 per million output tokens.
- What is MoonshotAI: Kimi K2.7 Code's context window?
- 262,144 tokens, roughly 393 pages of text in a single request.
- Does MoonshotAI: Kimi K2.7 Code support tool calling?
- It supports tool calling, structured output, a reasoning mode.
- Can MoonshotAI: Kimi K2.7 Code process images?
- Yes, it accepts image input.