Mathematics · Tencent

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

Hunyuan-Large scores 83.1 on MATH-500, placing it #145 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
83.1
0–100 scale
Rank
#145
of 600
Percentile
76th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
13.6
points

Score distribution

The chart shows the top 10 models on MATH-500, with Hunyuan-Large 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 sits at #145 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 13.6 points. The median model in this index scores 76.0, which puts Hunyuan-Large above the midpoint.

Tencent models average 74.0 on this benchmark. Hunyuan-Large is 9.1 points above that provider line, so it is a stronger result than the average Tencent model.

Among multimodal models, the average is 81.3. Hunyuan-Large is 1.8 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 83.1 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Hunyuan-Large Chat Tencent 200000 $4.35 78.1
Llama 4 Maverick Base Meta AI 128000 $4.68 79.1
Sonar Max Perplexity 32768 $11.60 77.8
Command A Pro Cohere 200000 $14.28 81.3
Hunyuan-Large Tencent 65536 $4.33 78.2
Hunyuan-Turbo Pro Tencent 65536 $12.00 77.6
Gemini 2.5 Pro Vision Google DeepMind 200000 $14.91 82.0

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
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
MMMU 75.7 143 76th
Arena Elo 1394.8 230 62th

FAQ

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

Hunyuan-Large scores 83.1 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Hunyuan-Large rank on MATH-500?

It ranks #145 of 600 models, in the 76th percentile. The leader is GPT-5.2 Max at 96.7.

Is Hunyuan-Large good at MATH-500?

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 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 cost?

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

Related