Llama 3.1 Turbo Instruct on HumanEval: score, rank and what it means
Llama 3.1 Turbo Instruct scores 79.2 on HumanEval, placing it #260 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with Llama 3.1 Turbo Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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, Llama 3.1 Turbo Instruct sits at #260 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 17.6 points. The median model in this index scores 77.4, which puts Llama 3.1 Turbo Instruct above the midpoint.
Together AI models average 68.4 on this benchmark. Llama 3.1 Turbo Instruct is 10.8 points above that provider line, so it is a stronger result than the average Together AI model.
Among multimodal models, the average is 82.2. Llama 3.1 Turbo Instruct is 3.0 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 79.2 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 $4.21 per million input tokens, Llama 3.1 Turbo Instruct is above 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3.1 Chat | Meta AI | 32768 | $3.82 | 75.3 |
| Llama 3.3 Groq Base | Groq | 16384 | $3.24 | 73.5 |
| Gemma 3 Chat | Google DeepMind | 65536 | $3.74 | 74.5 |
| Llama 3.1 Cerebras Base | Cerebras | 65536 | $3.36 | 72.7 |
| Llama 3.1 Turbo Instruct | Together AI | 32768 | $4.21 | 76.7 |
| Sonar Reasoning | Perplexity | 200000 | $11.48 | 76.2 |
| Fusion Max | OpenRouter | 65536 | $9.14 | 72.5 |
Other benchmarks for Llama 3.1 Turbo Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 80.3 | 176 | 71th | |
| GPQA Diamond | 73.4 | 191 | 68th | |
| SWE-bench Verified | 68.3 | 137 | 77th | |
| MATH-500 | 80.3 | 203 | 66th | |
| AIME 2025 | 70.5 | 249 | 59th | |
| LiveCodeBench | 66.9 | 255 | 58th | |
| IFEval | 86.0 | 158 | 74th | |
| TruthfulQA | 81.0 | 156 | 74th | |
| HellaSwag | 86.8 | 185 | 69th | |
| MMMU | 71.3 | 265 | 56th | |
| Arena Elo | 1417.0 | 161 | 73th |
FAQ
What score does Llama 3.1 Turbo Instruct get on HumanEval?
Llama 3.1 Turbo Instruct scores 79.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does Llama 3.1 Turbo Instruct rank on HumanEval?
It ranks #260 of 600 models, in the 57th percentile. The leader is GPT-5.2 Pro at 96.8.
Is Llama 3.1 Turbo Instruct good at HumanEval?
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 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 Llama 3.1 Turbo Instruct cost?
Llama 3.1 Turbo Instruct costs $4.21 per million input tokens and $17.73 per million output tokens.