Knowledge · Moonshot AI

Kimi K1.5 on MMLU-Pro: score, rank and what it means

Kimi K1.5 scores 82.7 on MMLU-Pro, placing it #109 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
82.7
0–100 scale
Rank
#109
of 600
Percentile
82th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
8.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Kimi K1.5 highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Kimi K1.5 sits at #109 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 8.9 points. The median model in this index scores 76.1, which puts Kimi K1.5 above the midpoint.

Moonshot AI models average 75.0 on this benchmark. Kimi K1.5 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 80.0. Kimi K1.5 is 2.7 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 82.7 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 $5.19 per million input tokens, Kimi K1.5 is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Kimi K1.5 Instruct Moonshot AI 200000 $5.15 80.5
Gemini 2.5 Pro Turbo Google DeepMind 1000000 $16.32 83.9
Doubao 1.5 Pro ByteDance 200000 $13.65 79.7
Claude Haiku 4.5 Vision Anthropic 128000 $13.01 79.2
Kimi K1.5 Moonshot AI 128000 $5.19 80.7
Kimi K2 Chat Moonshot AI 400000 $5.74 82.1
o3 Turbo OpenAI 200000 $16.63 83.4

Other benchmarks for Kimi K1.5

BenchmarkScoreRankPercentileRelative
GPQA Diamond 74.4 155 74th
SWE-bench Verified 68.2 141 77th
HumanEval 87.1 84 86th
MATH-500 85.3 103 83th
AIME 2025 80.8 77 87th
LiveCodeBench 71.1 168 72th
IFEval 87.9 104 83th
TruthfulQA 84.7 69 89th
HellaSwag 87.2 164 73th
MMMU 77.8 99 84th
Arena Elo 1432.2 117 81th

FAQ

What score does Kimi K1.5 get on MMLU-Pro?

Kimi K1.5 scores 82.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Kimi K1.5 rank on MMLU-Pro?

It ranks #109 of 600 models, in the 82nd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Kimi K1.5 good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 cost?

Kimi K1.5 costs $5.19 per million input tokens and $21.20 per million output tokens.

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