Mathematics · Moonshot AI

Kimi K1.5 Chat on MATH-500: score, rank and what it means

Kimi K1.5 Chat scores 81.7 on MATH-500, placing it #171 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
81.7
0–100 scale
Rank
#171
of 600
Percentile
72th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
15.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Kimi K1.5 Chat 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 K1.5 Chat sits at #171 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 15.0 points. The median model in this index scores 76.0, which puts Kimi K1.5 Chat above the midpoint.

Moonshot AI models average 74.0 on this benchmark. Kimi K1.5 Chat is 7.7 points above that provider line, so it is a stronger result than the average Moonshot AI model.

Among multimodal models, the average is 81.3. Kimi K1.5 Chat is 0.4 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 81.7 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 $5.11 per million input tokens, Kimi K1.5 Chat is above 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
ERNIE 4.0 Turbo Baidu 65536 $12.00 78.0
Llama 3.3 Instruct Meta AI 128000 $4.33 76.6
Sonar Pro Pro Perplexity 200000 $13.59 79.7
GLM-4.5 Zhipu AI 200000 $4.55 78.2
Kimi K1.5 Chat Moonshot AI 128000 $5.11 80.2
Magistral Instruct Mistral AI 65536 $4.48 78.4
Reka Flash Max Reka AI 32768 $11.17 75.9

Other benchmarks for Kimi K1.5 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.3 139 77th
GPQA Diamond 78.1 83 86th
SWE-bench Verified 69.9 111 82th
HumanEval 84.3 127 79th
AIME 2025 81.4 68 89th
LiveCodeBench 75.7 86 86th
IFEval 88.2 99 84th
TruthfulQA 80.3 171 72th
HellaSwag 87.2 165 73th
MMMU 73.6 202 66th
Arena Elo 1422.6 137 77th

FAQ

What score does Kimi K1.5 Chat get on MATH-500?

Kimi K1.5 Chat scores 81.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Kimi K1.5 Chat rank on MATH-500?

It ranks #171 of 600 models, in the 72nd percentile. The leader is GPT-5.2 Max at 96.7.

Is Kimi K1.5 Chat good at MATH-500?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 K1.5 Chat cost?

Kimi K1.5 Chat costs $5.11 per million input tokens and $26.59 per million output tokens.

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