Llama 3.1 Turbo 7B on Arena Elo: score, rank and what it means
Llama 3.1 Turbo 7B scores 1245.4 on Arena Elo, placing it #497 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 distribution
The chart shows the top 10 models on Arena Elo, with Llama 3.1 Turbo 7B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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, Llama 3.1 Turbo 7B sits at #497 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 256.5 points. The median model in this index scores 1373.8, which puts Llama 3.1 Turbo 7B below the midpoint.
Together AI models average 1312.2 on this benchmark. Llama 3.1 Turbo 7B is 66.8 points below that provider line, so it is a weaker result than the average Together AI model.
Among small open-weight models, the average is 1224.7. Llama 3.1 Turbo 7B is 20.7 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 1245.4 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 $0.98 per million input tokens, Llama 3.1 Turbo 7B is below 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Gemma 3 8B | Google DeepMind | 16384 | $0.96 | 56.5 |
| Mixtral Groq 8B | Groq | 32768 | $0.77 | 54.8 |
| Nemotron 4 8B | NVIDIA | 4096 | $1.06 | 57.9 |
| Mistral Small 3 7B | Mistral AI | 4096 | $0.89 | 55.2 |
| Llama 3.1 Turbo 7B | Together AI | 8192 | $0.98 | 56.4 |
| Llama 3 Hyperbolic 8B | Hyperbolic | 16384 | $0.92 | 56.0 |
| Nemotron 4 7B | NVIDIA | 16384 | $1.05 | 56.9 |
Other benchmarks for Llama 3.1 Turbo 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 63.8 | 474 | 21th | |
| GPQA Diamond | 51.9 | 500 | 17th | |
| SWE-bench Verified | 43.8 | 481 | 20th | |
| HumanEval | 59.0 | 512 | 15th | |
| MATH-500 | 55.8 | 510 | 15th | |
| AIME 2025 | 44.6 | 501 | 17th | |
| LiveCodeBench | 44.2 | 506 | 16th | |
| IFEval | 65.9 | 520 | 13th | |
| TruthfulQA | 63.0 | 491 | 18th | |
| HellaSwag | 72.0 | 499 | 17th | |
| MMMU | 56.7 | 476 | 21th |
FAQ
What score does Llama 3.1 Turbo 7B get on Arena Elo?
Llama 3.1 Turbo 7B scores 1245.4 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.
How does Llama 3.1 Turbo 7B rank on Arena Elo?
It ranks #497 of 600 models, in the 17th percentile. The leader is Claude Opus 4.5 Max at 1501.9.
Is Llama 3.1 Turbo 7B good at Arena Elo?
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 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 Llama 3.1 Turbo 7B cost?
Llama 3.1 Turbo 7B costs $0.98 per million input tokens and $4.14 per million output tokens.