Capability
65.5/100
field median 56.2
#34 of 232 ranked models
Kimi K2.7 Code
Released Jun 12, 2026 — see all recent releases
Decision reading
Kimi K2.7 Code scores 65.5 out of 100 and ranks #34 of 232. This profile shows 8 source-displayable benchmark rows; its strongest eligible category is Coding at #51. API pricing is $0.95 input and $4 output per million tokens.
Data as of September 10, 2026 · How the score is built
Share or export
Strongest published evidence
Coding ranks #51. Particularly well-suited for software development and code generation tasks.
Validate before choosing
8 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #72.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
$0.95input / $4 output
input median $1
blended $2.48
Speed
50tok/s
field median 86.5 tok/s
First token 47.89 s
Context
256Ktokens
field median 256,000
Reported for this model; direct source link not stored
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Kimi K2.7 Code category percentile values
- Agentic53rd percentile
- Coding67th percentile
- ReasoningNot eligible
- KnowledgeNot eligible
- MathNot eligible
- MultilingualNot eligible
- MultimodalNot eligible
- Instruction followingNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#72/152
- Coding#51/151
- ReasoningNot ranked
- KnowledgeNot ranked
- MathNot ranked
- MultilingualNot ranked
- MultimodalNot ranked
- Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelKimi K2.7 Code · 65.5 score · $2.48 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic3/3 verified
- Coding5/5 verified
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- MultimodalNot measured
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 256K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Kimi K2.7 Code needs ~640GB VRAM (8× NVIDIA H100 (80GB)).
- Rate limits
- Not tracked yet
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Kimi K2.7 Code
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #72 of 152Percentile 53rdWeight 22%3 benchmarksVerified | 46.8 | #72 of 152 | 53rd | 22% | 3 benchmarks | Verified |
| CodingRank #51 of 151Percentile 67thWeight 20%5 benchmarksVerified | 50.9 | #51 of 151 | 67th | 20% | 5 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| cursorBench32 | Score49.7% | Versus best verified row Best verified: Claude Fable 5.1 · 73.4% | Gap23.7 behind | WeightWeighted 10% | Benchmark exact |
| Kimi Code Bench v2 | Score62.0% | Versus best verified row Best verified: Kimi K3 · 72.9% | Gap10.9 behind | WeightDisplay only | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score53.6% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap39.4 behind | WeightDisplay only | Provider exact |
| MLS-Bench Lite | Score35.1% | Versus best verified row Best verified: Kimi K3 · 48.3% | Gap13.2 behind | WeightDisplay only | Provider exact |
| OpenHarmony BenchOpenHarmony Bench v1.0 | Score52.1% | Versus best verified row Best verified: Qwen3.8 Max · 60.8% | Gap8.7 behind | WeightDisplay only | Benchmark exact |
Agentic3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Kimi Claw 24/7Kimi Claw 24/7 Bench | Score46.9% | Versus best verified row Best verified: Kimi K2.7 Code · 46.9% | GapBest verified | WeightDisplay only | Provider exact |
| MCP Atlas | Score76% | Versus best verified row Best verified: Muse Spark 1.1 · 88.1% | Gap12.1 behind | WeightDisplay only | Provider exact |
| MCP Mark VerifiedMCPMark-Verified | Score81.1% | Versus best verified row Best verified: Kimi K2.7 Code · 81.1% | GapBest verified | WeightDisplay only | Provider exact |
Lineage
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Feb 1, 2026
Kimi K2.5Score 54.0 · $0.6 / $3
Apr 20, 2026
Kimi K2.6Score 65.4 · $0.95 / $4
Jun 12, 2026 · you are here
Kimi K2.7 CodeScore 65.5 · $0.95 / $4
Code
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Kimi K2.7 Code ranks #34 of 232 on the public leaderboard with a score of 65.49/100. It does not yet have enough sourced coverage for a verified position.
Kimi K2.7 Code is a open weight model with a 256K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Official exact-value snapshot from MoonshotAI's Kimi K2.7 Code Hugging Face model card. BenchLM stores the coding-agent showcase rows as display-only launch evidence because several metrics are provider-run or benchmark variants that are not part of the weighted public benchmark spine.
Its explicit predecessor is Kimi K2.6. 8 of 434 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #51, while its lowest eligible position is Agentic at #72. particularly well-suited for software development and code generation tasks.
Radar
Full release historyKimi K2.7 Code release history
Kimi K2.7 Code released
Moonshot AI · Model release
Source confirmed
Radar confirmed these at the source. Use Kimi K2.7 Code in your work? Explore Radar to follow supported changes and choose your alerts.
Frequently asked questions
How does Kimi K2.7 Code perform overall in AI benchmarks?
Kimi K2.7 Code ranks #34 out of 232 models on the public BenchAlign leaderboard, with a score of 65.49/100. Its evidence status is Estimated, and this profile shows 8 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Kimi K2.7 Code good for coding and programming?
Kimi K2.7 Code ranks #51 out of 151 eligible models for coding and programming, with a public category score of 50.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Kimi K2.7 Code good for agentic tool use and computer tasks?
Kimi K2.7 Code ranks #72 out of 152 eligible models for agentic tool use and computer tasks, with a public category score of 46.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Kimi K2.7 Code open source?
Kimi K2.7 Code is an open-weight model from Moonshot AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Does Kimi K2.7 Code have full benchmark coverage on BenchLM?
No. Kimi K2.7 Code currently has 24 source-displayable rows across 434 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Kimi K2.7 Code?
Kimi K2.7 Code has a reported context window of 256K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.
Compare Kimi K2.7 Code with every tracked model482 comparisons
Last updated September 10, 2026. Runtime fields remain blank until a sourced snapshot exists.
Watch Kimi K2.7 Code in the weekly brief
Get one weekly email when material rank, price, availability, or benchmark evidence changes are worth revisiting.
Read a sample issueJoin 2,000+ readers.