Knowledge · Moonshot AI

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

Kimi K1.5 Base scores 78.2 on MMLU-Pro, placing it #237 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
78.2
0–100 scale
Rank
#237
of 600
Percentile
61th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
13.4
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Kimi K1.5 Base 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 Base sits at #237 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 13.4 points. The median model in this index scores 76.1, which puts Kimi K1.5 Base above the midpoint.

Moonshot AI models average 75.0 on this benchmark. Kimi K1.5 Base is 3.2 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 Base is 1.8 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 78.2 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 $4.34 per million input tokens, Kimi K1.5 Base 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
Mistral Small 3 Instruct Mistral AI 32768 $3.97 75.1
QwQ Alibaba Cloud 128000 $4.57 78.6
Qwen3-Coder Base Alibaba Cloud 200000 $3.99 76.6
Reka Core Turbo Reka AI 32768 $12.58 78.4
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Nova Lite Amazon 65536 $9.20 73.4

Other benchmarks for Kimi K1.5 Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 74.3 160 73th
SWE-bench Verified 67.3 162 73th
HumanEval 82.2 181 70th
MATH-500 79.9 211 65th
AIME 2025 72.9 204 66th
LiveCodeBench 67.0 250 58th
IFEval 86.0 157 74th
TruthfulQA 81.2 149 75th
HellaSwag 85.8 223 63th
MMMU 76.3 133 78th
Arena Elo 1397.5 216 64th

FAQ

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

Kimi K1.5 Base scores 78.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

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

It ranks #237 of 600 models, in the 61st percentile. The leader is GPT-5.2 Pro at 91.6.

Is Kimi K1.5 Base 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 Base cost?

Kimi K1.5 Base costs $4.34 per million input tokens and $15.70 per million output tokens.

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