Kimi
Released June 12, 2026

Kimi K2.7 Code

Kimi K2.7 Code by Kimi: thinking-only agentic coding MoE, 1T params (32B active), 256K context, native multimodality, 30% fewer thinking tokens than K2.6.

Inputs
Text
Image
Video
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Kimi K2.7 Code - Thinking-only agentic coding MoE with reduced overthinking

Kimi K2.7 Code is Kimi's dedicated coding model, built on K2.6 with a focus on long-horizon coding task completion and instruction compliance in extended contexts. Its defining characteristic is that it operates exclusively in thinking mode - non-thinking mode is unsupported and disabling it causes an API error.

The model reduces overthinking tendencies by 30% on average compared to K2.6, using fewer thinking tokens while improving task success rates. It also improves agentic capabilities by 10% over K2.6.

TraitDetail
Thinking-only modeNo non-thinking mode available; disabling thinking causes an API error
Reduced overthinking~30% fewer thinking tokens than K2.6 on average
Architecture1T-parameter MoE with 32B active, 384 experts, 8 selected per token, 1 shared expert
Native INT4 quantizationMoE weights stored in INT4; BF16 for non-MoE layers
Multimodal inputMoonViT vision encoder supports text, image, and video input
Fixed samplingtemperature locked at 1.0, top_p at 0.95, n at 1, penalties at 0.0
HighSpeed variantSame model at ~180 tokens/s, up to 260 tokens/s in short contexts
Context window256K tokens

Long-horizon coding and agentic tool use

Kimi K2.7 Code supports multi-step tool invocation and reasoning, combining visual understanding with function calling. The model targets complex logical reasoning, mathematical problems, and code writing within its 256K context window.

Benchmark Performance

Independent evaluations · Artificial Analysis

25.8%
Intelligence
60.8%
Coding Index
21.0%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science89.6%
Humanity's Last Exam35.0%
SciCode - Scientific Coding47.8%
Instruction Following63.1%
Long Context Reasoning79.3%
τ²-Bench - Agentic Tasks90.1%
TerminalBench - System Control44.7%

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderKimiAnthropicAnthropic
Release DateJune 12, 2026September 22, 2026September 28, 2026
Knowledge Cutoff--Jun 2026
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.95
Best Input Pricing
$4$2
Output Pricing
$4
Best Output Pricing
$20$10
Modalities
Inputs
textimagevideo
textimagefile
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index25.8
57.6
Best Intelligence Index
56.0
Coding Index60.8--
Agentic Index21.0--
Kimi K2.7 Code
Claude Opus 5.5
Claude Sonnet 5.5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

35%
Kimi K2.7 Code
Humanity's Last Exam
Score: 35%
Kimi K2.7 Code
61%
Claude Opus 5.5
Humanity's Last Exam
Score: 61%
Claude Opus 5.5
55%
Claude Sonnet 5.5
Humanity's Last Exam
Score: 55%
Claude Sonnet 5.5

Long Context Reasoning

Logical reasoning over long context windows.

79%
Kimi K2.7 Code
Long Context Reasoning
Score: 79%
Kimi K2.7 Code
85%
Claude Opus 5.5
Long Context Reasoning
Score: 85%
Claude Opus 5.5
83%
Claude Sonnet 5.5
Long Context Reasoning
Score: 83%
Claude Sonnet 5.5

SciCode Benchmark

Scientific coding and mathematical modeling.

48%
Kimi K2.7 Code
SciCode Benchmark
Score: 48%
Kimi K2.7 Code
67%
Claude Opus 5.5
SciCode Benchmark
Score: 67%
Claude Opus 5.5
61%
Claude Sonnet 5.5
SciCode Benchmark
Score: 61%
Claude Sonnet 5.5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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