Preference · Tencent

Hunyuan-Large Instruct on Arena Elo: score, rank and what it means

Hunyuan-Large Instruct scores 1422.1 on Arena Elo, placing it #138 of 600 models in the index. The benchmark average is 1349.9 and the leader is Claude Opus 4.5 Max at 1501.9.

Score
1422.1
0–100 scale
Rank
#138
of 600
Percentile
77th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
79.8
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Hunyuan-Large Instruct highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Max 1501.9
GPT-5.2 Reasoning 1500.4
GPT-5.2 Turbo 1500.3
Claude Opus 4.5 Reasoning 1497.5
GPT-5.2 Max 1495.3
Gemini 3 Pro Turbo 1494.9
Grok 4 Max 1491.4
Claude Opus 4.5 1491.2
GPT-5.1 Pro 1490.0
Grok 4 Reasoning 1487.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
2 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
3 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
6 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
7 Grok 4 Max xAI 2000000 $19.70 86.6
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
10 Grok 4 Reasoning xAI 2000000 $19.67 87.8

What this score means

On Arena Elo, Hunyuan-Large Instruct sits at #138 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 79.8 points. The median model in this index scores 1373.8, which puts Hunyuan-Large Instruct above the midpoint.

Tencent models average 1357.4 on this benchmark. Hunyuan-Large Instruct is 64.7 points above that provider line, so it is a stronger result than the average Tencent model.

Among multimodal models, the average is 1409.6. Hunyuan-Large Instruct is 12.5 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 1422.1 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 $4.39 per million input tokens, Hunyuan-Large Instruct is above the median input price of $4.00 across the 600 models scored on Arena Elo. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.0 Turbo Baidu 65536 $12.00 78.0
GPT-5.1 Mini OpenAI 128000 $12.19 77.7
Reka Core Reka AI 32768 $12.17 77.4
Kimi K1.5 Chat Moonshot AI 128000 $5.11 80.2
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2
Claude Haiku 4.5 Anthropic 1000000 $13.86 79.4
GLM-4.6 Base Zhipu AI 128000 $4.53 78.5

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
MATH-500 82.9 148 75th
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

FAQ

What score does Hunyuan-Large Instruct get on Arena Elo?

Hunyuan-Large Instruct scores 1422.1 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Hunyuan-Large Instruct rank on Arena Elo?

It ranks #138 of 600 models, in the 77th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Hunyuan-Large Instruct good at Arena Elo?

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 Arena Elo score calculated?

Arena Elo is a preference 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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