Llama 3.1 Cerebras 7B on HellaSwag: score, rank and what it means
Llama 3.1 Cerebras 7B scores 73.7 on HellaSwag, placing it #461 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.
Score distribution
The chart shows the top 10 models on HellaSwag, with Llama 3.1 Cerebras 7B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 5 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 8 | Gemini 3 Pro Turbo | Google DeepMind | 400000 | $19.62 | 86.4 |
| 9 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 10 | o4 Pro | OpenAI | 1000000 | $19.37 | 87.3 |
What this score means
On HellaSwag, Llama 3.1 Cerebras 7B sits at #461 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 22.4 points. The median model in this index scores 83.6, which puts Llama 3.1 Cerebras 7B below the midpoint.
Cerebras models average 79.4 on this benchmark. Llama 3.1 Cerebras 7B is 5.7 points below that provider line, so it is a weaker result than the average Cerebras model.
Among small open-weight models, the average is 70.2. Llama 3.1 Cerebras 7B is 3.5 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 73.7 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 $0.95 per million input tokens, Llama 3.1 Cerebras 7B is below the median input price of $4.00 across the 600 models scored on HellaSwag. 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 |
|---|---|---|---|---|
| Codestral 7B | Mistral AI | 32768 | $1.05 | 57.0 |
| Firefunction Nano | Fireworks AI | 16384 | $3.07 | 58.1 |
| Pythia Instruct | EleutherAI | 8192 | $1.41 | 60.8 |
| Llama 3 Anyscale 7B | Anyscale | 4096 | $0.98 | 56.2 |
| Llama 3.1 Cerebras 7B | Cerebras | 32768 | $0.95 | 56.5 |
| Llama 4 Scout 8B | Meta AI | 8192 | $1.46 | 61.2 |
| MiniMax-Text 7B | MiniMax | 16384 | $1.10 | 57.7 |
Other benchmarks for Llama 3.1 Cerebras 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 62.9 | 490 | 18th | |
| GPQA Diamond | 51.7 | 502 | 16th | |
| SWE-bench Verified | 41.5 | 506 | 16th | |
| HumanEval | 60.3 | 500 | 17th | |
| MATH-500 | 55.8 | 509 | 15th | |
| AIME 2025 | 44.6 | 500 | 17th | |
| LiveCodeBench | 47.3 | 472 | 21th | |
| IFEval | 69.2 | 472 | 21th | |
| TruthfulQA | 61.9 | 506 | 16th | |
| MMMU | 52.4 | 525 | 13th | |
| Arena Elo | 1262.0 | 471 | 22th |
FAQ
What score does Llama 3.1 Cerebras 7B get on HellaSwag?
Llama 3.1 Cerebras 7B scores 73.7 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.
How does Llama 3.1 Cerebras 7B rank on HellaSwag?
It ranks #461 of 600 models, in the 23rd percentile. The leader is GPT-5.2 Max at 96.1.
Is Llama 3.1 Cerebras 7B good at HellaSwag?
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 HellaSwag score calculated?
HellaSwag is a commonsense 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 Cerebras 7B cost?
Llama 3.1 Cerebras 7B costs $0.95 per million input tokens and $4.53 per million output tokens.