Mathematics · Moonshot AI

Kimi K2 7B on MATH-500: score, rank and what it means

Kimi K2 7B scores 64.6 on MATH-500, placing it #421 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
64.6
0–100 scale
Rank
#421
of 600
Percentile
30th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
32.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Kimi K2 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Kimi K2 7B sits at #421 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 32.1 points. The median model in this index scores 76.0, which puts Kimi K2 7B below the midpoint.

Moonshot AI models average 74.0 on this benchmark. Kimi K2 7B is 9.4 points below that provider line, so it is a weaker result than the average Moonshot AI model.

Among small open-weight models, the average is 53.7. Kimi K2 7B is 10.9 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 64.6 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.72 per million input tokens, Kimi K2 7B is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nova Pro Nano Amazon 8192 $5.44 65.4
Zephyr Hugging Face 8192 $1.61 62.8
GPT-NeoX Instruct EleutherAI 16384 $1.52 62.6
Embed 4 Max Cohere 8192 $5.68 66.1
Kimi K2 7B Moonshot AI 16384 $1.72 62.7
GLM-4.5 8B Zhipu AI 32768 $1.46 61.3
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4

Other benchmarks for Kimi K2 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 66.5 431 28th
GPQA Diamond 57.0 440 27th
SWE-bench Verified 52.5 401 33th
HumanEval 67.5 416 31th
AIME 2025 51.1 450 25th
LiveCodeBench 50.4 444 26th
IFEval 75.0 398 34th
TruthfulQA 67.9 414 31th
HellaSwag 78.1 400 33th
MMMU 59.2 437 27th
Arena Elo 1304.4 412 31th

FAQ

What score does Kimi K2 7B get on MATH-500?

Kimi K2 7B scores 64.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Kimi K2 7B rank on MATH-500?

It ranks #421 of 600 models, in the 30th percentile. The leader is GPT-5.2 Max at 96.7.

Is Kimi K2 7B good at MATH-500?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the MATH-500 score calculated?

MATH-500 is a mathematics benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Kimi K2 7B cost?

Kimi K2 7B costs $1.72 per million input tokens and $8.97 per million output tokens.

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