Coding · Tencent

Hunyuan-Large 1.5B on HumanEval: score, rank and what it means

Hunyuan-Large 1.5B scores 55.1 on HumanEval, placing it #543 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
55.1
0–100 scale
Rank
#543
of 600
Percentile
10th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
41.7
points

Score distribution

The chart shows the top 10 models on HumanEval, with Hunyuan-Large 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Hunyuan-Large 1.5B sits at #543 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 41.7 points. The median model in this index scores 77.4, which puts Hunyuan-Large 1.5B below the midpoint.

Tencent models average 75.8 on this benchmark. Hunyuan-Large 1.5B is 20.7 points below that provider line, so it is a weaker result than the average Tencent model.

Among small open-weight models, the average is 56.7. Hunyuan-Large 1.5B is 1.6 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 55.1 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 $0.54 per million input tokens, Hunyuan-Large 1.5B is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Embed 4 Nano Cohere 8192 $1.48 49.7
Kimi K1.5 1.5B Moonshot AI 4096 $0.75 53.2
Mixtral Turbo 7B Together AI 8192 $0.68 53.2
Hunyuan-Large 1.5B Tencent 8192 $0.54 50.5
Nemotron 4 1.5B NVIDIA 32768 $0.49 50.8
DBRX 8B Databricks 4096 $0.82 54.1

Other benchmarks for Hunyuan-Large 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 56.6 562 6th
GPQA Diamond 49.3 532 11th
SWE-bench Verified 34.1 563 6th
MATH-500 49.1 562 6th
AIME 2025 35.7 561 7th
LiveCodeBench 36.6 560 7th
IFEval 63.6 542 10th
TruthfulQA 56.7 555 8th
HellaSwag 66.7 566 6th
MMMU 51.5 539 10th
Arena Elo 1213.8 540 10th

FAQ

What score does Hunyuan-Large 1.5B get on HumanEval?

Hunyuan-Large 1.5B scores 55.1 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Hunyuan-Large 1.5B rank on HumanEval?

It ranks #543 of 600 models, in the 10th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Hunyuan-Large 1.5B good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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 1.5B cost?

Hunyuan-Large 1.5B costs $0.54 per million input tokens and $2.78 per million output tokens.

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