Mathematics · Moonshot AI

Kimi K2 8B on MATH-500: score, rank and what it means

Kimi K2 8B scores 68.7 on MATH-500, placing it #392 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
68.7
0–100 scale
Rank
#392
of 600
Percentile
35th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
28.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Kimi K2 8B 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 8B sits at #392 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 28.0 points. The median model in this index scores 76.0, which puts Kimi K2 8B below the midpoint.

Moonshot AI models average 74.0 on this benchmark. Kimi K2 8B is 5.3 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 8B is 15.0 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 68.7 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 $1.86 per million input tokens, Kimi K2 8B 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
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Sonar Pro Nano Perplexity 32768 $5.50 66.1
Command A Nano Cohere 8192 $5.90 66.3
Embed 4 Turbo Cohere 4096 $5.13 64.0
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Molmo Instruct Allen Institute for AI 32768 $2.53 68.3
Firesearch Fireworks AI 32768 $7.03 68.5

Other benchmarks for Kimi K2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.3 427 29th
GPQA Diamond 59.3 411 32th
SWE-bench Verified 50.9 414 31th
HumanEval 69.9 395 34th
AIME 2025 55.4 414 31th
LiveCodeBench 55.0 406 32th
IFEval 75.4 394 34th
TruthfulQA 69.4 404 33th
HellaSwag 78.6 398 34th
MMMU 62.2 406 32th
Arena Elo 1311.4 406 32th

FAQ

What score does Kimi K2 8B get on MATH-500?

Kimi K2 8B scores 68.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Kimi K2 8B rank on MATH-500?

It ranks #392 of 600 models, in the 35th percentile. The leader is GPT-5.2 Max at 96.7.

Is Kimi K2 8B 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 8B cost?

Kimi K2 8B costs $1.86 per million input tokens and $10.03 per million output tokens.

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