Hunyuan-Large Instruct on IFEval: score, rank and what it means
Hunyuan-Large Instruct scores 86.1 on IFEval, placing it #151 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.
Score distribution
The chart shows the top 10 models on IFEval, with Hunyuan-Large Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 2 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 6 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 7 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
| 8 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 9 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 10 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
What this score means
On IFEval, Hunyuan-Large Instruct sits at #151 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 10.0 points. The median model in this index scores 81.2, which puts Hunyuan-Large Instruct above the midpoint.
Tencent models average 79.6 on this benchmark. Hunyuan-Large Instruct is 6.5 points above that provider line, so it is a stronger result than the average Tencent model.
Among multimodal models, the average is 85.2. Hunyuan-Large Instruct is 0.9 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 86.1 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 IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| GLM-4.6 | Zhipu AI | 128000 | $5.10 | 80.2 |
| Nova Pro Max | Amazon | 1000000 | $14.05 | 81.2 |
| Gemini 3 Pro Mini | Google DeepMind | 128000 | $12.27 | 78.1 |
| Kimi K1.5 Instruct | Moonshot AI | 200000 | $5.15 | 80.5 |
| Hunyuan-Large Instruct | Tencent | 65536 | $4.39 | 78.2 |
| Magistral | Mistral AI | 200000 | $4.75 | 79.8 |
| MiniMax-M2 | MiniMax | 200000 | $5.19 | 80.6 |
Other benchmarks for Hunyuan-Large Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| 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 | |
| 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 IFEval?
Hunyuan-Large Instruct scores 86.1 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.
How does Hunyuan-Large Instruct rank on IFEval?
It ranks #151 of 600 models, in the 75th percentile. The leader is Claude Opus 4.5 Pro at 96.1.
Is Hunyuan-Large Instruct good at IFEval?
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 IFEval score calculated?
IFEval is a instruction following 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.