Multimodal · Moonshot AI

Kimi K1.5 on MMMU: score, rank and what it means

Kimi K1.5 scores 77.8 on MMMU, placing it #99 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
77.8
0–100 scale
Rank
#99
of 600
Percentile
84th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
9.1
points

Score distribution

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

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

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-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Kimi K1.5 sits at #99 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 9.1 points. The median model in this index scores 70.0, which puts Kimi K1.5 above the midpoint.

Moonshot AI models average 68.9 on this benchmark. Kimi K1.5 is 8.9 points above that provider line, so it is a stronger result than the average Moonshot AI model.

Among multimodal models, the average is 74.3. Kimi K1.5 is 3.5 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 77.8 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 MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.5 Max Baidu 128000 $14.41 80.6
Gemini 2.5 Pro Pro Google DeepMind 400000 $17.16 83.6
ERNIE 4.5 Baidu 65536 $13.44 80.0
MiniMax-M2 MiniMax 200000 $5.19 80.6
Kimi K1.5 Moonshot AI 128000 $5.19 80.7
Nova Pro Amazon 32768 $12.75 79.4
Claude Haiku 4.5 Turbo Anthropic 200000 $14.37 80.0

Other benchmarks for Kimi K1.5

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.7 109 82th
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
Arena Elo 1432.2 117 81th

FAQ

What score does Kimi K1.5 get on MMMU?

Kimi K1.5 scores 77.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Kimi K1.5 rank on MMMU?

It ranks #99 of 600 models, in the 84th percentile. The leader is GPT-5.2 Max at 86.9.

Is Kimi K1.5 good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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