Mathematics · Tencent

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

Hunyuan-Turbo Pro scores 83.1 on MATH-500, placing it #146 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
#146
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-Turbo Pro 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-Turbo Pro sits at #146 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-Turbo Pro above the midpoint.

Tencent models average 74.0 on this benchmark. Hunyuan-Turbo Pro 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-Turbo Pro 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 $12.00 per million input tokens, Hunyuan-Turbo Pro 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
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
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2

Other benchmarks for Hunyuan-Turbo Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.9 150 75th
GPQA Diamond 75.9 122 80th
SWE-bench Verified 64.1 231 62th
HumanEval 83.2 156 74th
AIME 2025 73.4 198 67th
LiveCodeBench 72.6 135 78th
IFEval 83.2 239 60th
TruthfulQA 78.7 227 62th
HellaSwag 85.0 243 60th
MMMU 73.2 212 65th
Arena Elo 1403.3 200 67th

FAQ

What score does Hunyuan-Turbo Pro get on MATH-500?

Hunyuan-Turbo Pro 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-Turbo Pro rank on MATH-500?

It ranks #146 of 600 models, in the 76th percentile. The leader is GPT-5.2 Max at 96.7.

Is Hunyuan-Turbo Pro 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-Turbo Pro cost?

Hunyuan-Turbo Pro costs $12.00 per million input tokens and $51.23 per million output tokens.

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