Mathematics · Tencent

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

Hunyuan-Large Instruct scores 82.9 on MATH-500, placing it #148 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
82.9
0–100 scale
Rank
#148
of 600
Percentile
75th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
13.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Hunyuan-Large Instruct 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 Instruct sits at #148 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 13.8 points. The median model in this index scores 76.0, which puts Hunyuan-Large Instruct above the midpoint.

Tencent models average 74.0 on this benchmark. Hunyuan-Large Instruct is 9.0 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 Instruct is 1.6 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 82.9 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 $4.39 per million input tokens, Hunyuan-Large Instruct 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
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
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2
GLM-4.5 Chat Zhipu AI 65536 $4.53 78.3
Llama 3.1 Meta AI 200000 $4.16 76.3

Other benchmarks for Hunyuan-Large Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.0 209 65th
GPQA Diamond 75.4 136 77th
SWE-bench Verified 66.1 191 68th
HumanEval 84.0 132 78th
AIME 2025 76.9 130 78th
LiveCodeBench 68.3 219 64th
IFEval 86.1 151 75th
TruthfulQA 79.8 187 69th
HellaSwag 87.7 153 75th
MMMU 74.3 176 71th
Arena Elo 1422.1 138 77th

FAQ

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

Hunyuan-Large Instruct scores 82.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Hunyuan-Large Instruct rank on MATH-500?

It ranks #148 of 600 models, in the 75th percentile. The leader is GPT-5.2 Max at 96.7.

Is Hunyuan-Large Instruct 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 Instruct cost?

Hunyuan-Large Instruct costs $4.39 per million input tokens and $19.44 per million output tokens.

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