Mathematics · Tencent

Hunyuan-Large 7B on MATH-500: score, rank and what it means

Hunyuan-Large 7B scores 56.7 on MATH-500, placing it #499 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
56.7
0–100 scale
Rank
#499
of 600
Percentile
17th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
40.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Hunyuan-Large 7B 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, Hunyuan-Large 7B sits at #499 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 40.0 points. The median model in this index scores 76.0, which puts Hunyuan-Large 7B below the midpoint.

Tencent models average 74.0 on this benchmark. Hunyuan-Large 7B is 17.2 points below that provider line, so it is a weaker result than the average Tencent model.

Among small open-weight models, the average is 53.7. Hunyuan-Large 7B is 3.0 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 56.7 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 $1.08 per million input tokens, Hunyuan-Large 7B is below 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
Llama 3 DeepInfra 8B DeepInfra 8192 $1.05 57.4
Yi-Large 7B 01.AI 4096 $0.83 55.0
Codestral 7B Mistral AI 32768 $1.05 57.0
DeepSeek-Coder 7B DeepSeek 32768 $1.14 57.3
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Mistral Large 3 1.5B Mistral AI 32768 $0.82 55.4
Llama 3 Novita 7B Novita AI 8192 $0.92 56.3

Other benchmarks for Hunyuan-Large 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.0 471 22th
GPQA Diamond 56.3 446 26th
SWE-bench Verified 44.2 476 21th
HumanEval 61.6 472 21th
AIME 2025 43.6 515 14th
LiveCodeBench 44.5 503 16th
IFEval 69.9 462 23th
TruthfulQA 63.4 484 19th
HellaSwag 71.7 505 16th
MMMU 58.6 448 25th
Arena Elo 1251.8 488 19th

FAQ

What score does Hunyuan-Large 7B get on MATH-500?

Hunyuan-Large 7B scores 56.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Hunyuan-Large 7B rank on MATH-500?

It ranks #499 of 600 models, in the 17th percentile. The leader is GPT-5.2 Max at 96.7.

Is Hunyuan-Large 7B good at MATH-500?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 Hunyuan-Large 7B cost?

Hunyuan-Large 7B costs $1.08 per million input tokens and $5.56 per million output tokens.

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