Moonshot AI · multimodal · Released 2026-10-11

Kimi K2 Chat: pricing, context window and benchmarks

Kimi K2 Chat is a multimodal model from Moonshot AI. It offers a 400,000-token context window, costs $5.74 per million input tokens and $22.24 per million output tokens, and averages 82.1 across the index's benchmark suite.

reasoningcodingvisionlong contextopen weightsmultimodal
Input price
$5.74
per 1M tokens
Output price
$22.24
per 1M tokens
Context
400,000
tokens
Avg score
82.1
rank #84 of 600
Arena Elo
1445.6
modelled
Max output
4,096
tokens

Pricing

Kimi K2 Chat costs $5.74 per million input tokens and $22.24 per million output tokens. A blended 3:1 input-to-output mix works out to about $9.86 per million tokens. Cached input is listed at $0.54 per million tokens.

ItemPriceNotes
Input$5.74per 1M tokens
Output$22.24per 1M tokens
Cached input$0.54per 1M tokens
Blended 3:1$9.86estimate per 1M tokens
1M in + 1M out$27.98estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.7 110 82th
GPQA Diamond 77.4 99 84th
SWE-bench Verified 70.0 110 82th
HumanEval 88.1 71 88th
MATH-500 84.8 112 81th
AIME 2025 84.1 48 92th
LiveCodeBench 74.5 100 83th
IFEval 88.0 101 83th
TruthfulQA 82.8 111 82th
HellaSwag 91.6 46 92th
MMMU 79.6 64 89th
Arena Elo 1445.6 89 85th

What Kimi K2 Chat is good for

Kimi K2 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.74 per million input tokens, it sits in the mid-range of the index, and the 400,000-token context window is enough for large files and multi-file diffs.

Strengths

  • Large 400,000-token context window for long documents and agent traces.
  • Open weights make self-hosting, fine-tuning and data-residency review possible.
  • Accepts more than text, including image input where the provider supports it.
  • Reasoning-oriented profile, useful for multi-step problems and structured analysis.
  • Coding benchmarks are a relative strength within its tier.

Trade-offs

  • No standout weakness in the indexed specifications, but real-world behaviour still needs testing.

How it compares

ModelProviderContextInput / 1MAvg score
Claude 3.7 Sonnet Turbo Anthropic 200000 $15.56 82.3
Kimi K2 Instruct Moonshot AI 1000000 $5.80 82.3
Kimi K2 Chat Moonshot AI 400000 $5.74 82.1
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Gemini 2.5 Pro Vision Google DeepMind 200000 $14.91 82.0
Gemini 3 Flash Vision Google DeepMind 400000 $15.06 81.9

Browse all comparisons →

FAQ

How much does Kimi K2 Chat cost?

Kimi K2 Chat is listed at $5.74 per million input tokens and $22.24 per million output tokens. Cached input is $0.54 per million tokens. A blended 3:1 input-to-output mix is about $9.86 per million tokens.

What is the context window of Kimi K2 Chat?

Kimi K2 Chat has a context window of 400,000 tokens and can emit up to 4,096 output tokens per request in this index.

Is Kimi K2 Chat open weights?

Yes. Kimi K2 Chat is listed as an open-weight model under a open weights licence.

How does Kimi K2 Chat score on benchmarks?

Kimi K2 Chat averages 82.1 across the scored benchmarks in this index, ranking #84 of 600 models. Its strongest relative result is Arena Elo at 1445.6.

What is Kimi K2 Chat best for?

Kimi K2 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.74 per million input tokens, it sits in the mid-range of the index, and the 400,000-token context window is enough for large files and multi-file diffs.

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