Multimodal · Tencent

Hunyuan-Large on MMMU: score, rank and what it means

Hunyuan-Large scores 75.7 on MMMU, placing it #143 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
75.7
0–100 scale
Rank
#143
of 600
Percentile
76th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
11.2
points

Score distribution

The chart shows the top 10 models on MMMU, with Hunyuan-Large 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, Hunyuan-Large sits at #143 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 11.2 points. The median model in this index scores 70.0, which puts Hunyuan-Large above the midpoint.

Tencent models average 68.9 on this benchmark. Hunyuan-Large is 6.8 points above that provider line, so it is a stronger result than the average Tencent model.

Among multimodal models, the average is 74.3. Hunyuan-Large is 1.4 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 75.7 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 $4.33 per million input tokens, Hunyuan-Large 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
Codestral Mistral AI 65536 $4.19 77.6
DeepSeek-V3.2 Chat DeepSeek 1000000 $5.80 82.5
Qwen3 Base Alibaba Cloud 65536 $4.33 77.4
Mistral Large 3 Base Mistral AI 65536 $4.47 78.2
Hunyuan-Large Tencent 65536 $4.33 78.2
Hunyuan-Turbo Turbo Tencent 65536 $11.60 77.4
QwQ Chat Alibaba Cloud 65536 $4.28 78.2

Other benchmarks for Hunyuan-Large

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.7 157 74th
GPQA Diamond 75.0 146 76th
SWE-bench Verified 67.8 149 75th
HumanEval 82.1 184 69th
MATH-500 83.1 145 76th
AIME 2025 74.3 170 72th
LiveCodeBench 71.8 151 75th
IFEval 84.4 204 66th
TruthfulQA 80.9 160 73th
HellaSwag 84.6 262 56th
Arena Elo 1394.8 230 62th

FAQ

What score does Hunyuan-Large get on MMMU?

Hunyuan-Large scores 75.7 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Hunyuan-Large rank on MMMU?

It ranks #143 of 600 models, in the 76th percentile. The leader is GPT-5.2 Max at 86.9.

Is Hunyuan-Large 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 Hunyuan-Large cost?

Hunyuan-Large costs $4.33 per million input tokens and $20.11 per million output tokens.

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