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Llama 3.1-8B
About Llama 3.1-8B
Llama 3.1-8B is an AI model developed by Meta AI, in the language category, released in 2024, made available as an open-weights model with 8B params.
On this page you'll find Llama 3.1-8B's full specifications, including 67 benchmark results. Review provider pricing and benchmark scores below, or compare Llama 3.1-8B head-to-head with other language models.
Links
Run Llama 3.1-8B locally — what to buy
Share this build ↗Sized to what Llama 3.1-8B actually needs (~8k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.
Software support
✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.
Community
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Llama 3.1-8B benchmark scores▶
| Benchmark | Category | Score | Variant |
|---|---|---|---|
| HumanEval | code | 86.3% | instruct-pass@10-cited-tulu3 |
| HumanEval | code | 85.32% | instruct-cited-granite-3-2 |
| HumanEval | code | 66.5% | instruct-cited-phi35moe |
| HumanEval+ | code | 82.9% | instruct-pass@10-cited-tulu3 |
| HumanEval+ | code | 80.15% | instruct-cited-granite-3-2 |
| MBPP | code | 69.4% | instruct-cited-phi35moe |
| AlpacaEval 2 | general | 27.22% | instruct-cited-granite-3-2 |
| AlpacaEval 2 | general | 25.7% | instruct-cited-exaone35 |
| AlpacaEval 2 | general | 24.2% | instruct-lc-win-cited-tulu3 |
| ArenaHard | general | 36.43% | instruct-cited-granite-3-2 |
| ArenaHard | general | 27.7% | instruct-cited-exaone35 |
| ArenaHard | general | 25.7% | instruct-cited-phi35moe |
| IFEval | general | 80.6% | instruct-cited-tulu3 |
| IFEval | general | 79.1% | instruct-cited-granite-3-2 |
| IFEval | general | 78.8% | instruct-cited-falcon3 |
| IFEval | general | 12.7% | base-cited-falcon-mamba |
| LiveBench | general | 28.3 | instruct-cited-exaone35 |
| MMLU | general | 71.2% | instruct-cited-tulu3 |
| MMLU | general | 69.15% | instruct-cited-granite-3-2 |
| MMLU | general | 68.2% | instruct-5-shot-cited-falcon3 |
| MMLU | general | 68.1% | instruct-cited-phi35moe |
| MMLU | general | 66.9% | base-cited-olmo2 |
| MMLU | general | 66.4% | base-5-shot-cited-marin |
| MMLU-Pro | general | 44% | instruct-cited-phi35moe |
| MMLU-Pro | general | 36.4% | instruct-5-shot-cited-falcon3 |
| MMLU-Pro | general | 34.7% | base-cited-olmo2 |
| MMLU-Pro | general | 33.3% | base-cited-marin |
| MMLU-Pro | general | 24.95% | base-cited-falcon-mamba |
| MMMLU | general | 56.2% | instruct-cited-phi35moe |
| AGIEval | knowledge | 51.3 | base-cited-olmo2 |
| ARC-Challenge | knowledge | 79.5 | base-cited-olmo2 |
| ARC-Challenge | knowledge | 58.9 | base-cited-marin |
| ARC-Challenge | knowledge | 58.6 | instruct-25-shot-cited-falcon3 |
| ARC-Easy | knowledge | 85.8 | base-cited-marin |
| TriviaQA | knowledge | 80.3 | base-cited-olmo2 |
| GSM8K | math | 83.4% | instruct-cited-tulu3 |
| GSM8K | math | 83.24% | instruct-cited-granite-3-2 |
| GSM8K | math | 82.6% | instruct-5-shot-cited-falcon3 |
| GSM8K | math | 56.5% | base-cited-olmo2 |
| GSM8K | math | 47.92% | base-cited-falcon-mamba |
| MATH | math | 47.6% | instruct-cited-phi35moe |
| MATH | math | 42.5% | instruct-cited-tulu3 |
| MGSM | math | 56.7 | instruct-cited-phi35moe |
| BIG-Bench Hard | reasoning | 72.66% | instruct-cited-granite-3-2 |
| BIG-Bench Hard | reasoning | 63.4% | instruct-cited-phi35moe |
| BIG-Bench Hard | reasoning | 62.8% | instruct-cited-tulu3 |
| BIG-Bench Hard | reasoning | 48.6% | instruct-3-shot-cited-falcon3 |
| BIG-Bench Hard | reasoning | 46.4% | base-cited-marin |
| BIG-Bench Hard | reasoning | 25.29% | base-cited-falcon-mamba |
| DROP | reasoning | 61.5% | instruct-cited-tulu3 |
| DROP | reasoning | 61.48% | instruct-cited-granite-3-2 |
| DROP | reasoning | 56.4% | base-cited-olmo2 |
| GPQA Diamond | reasoning | 33.5% | instruct-0-shot-cited-falcon3 |
| GPQA Diamond | reasoning | 26.3% | instruct-cited-phi35moe |
| GPQA Diamond | reasoning | 6.15% | base-cited-falcon-mamba |
| HellaSwag | reasoning | 81.9 | base-10-shot-cited-marin |
| HellaSwag | reasoning | 81.6 | base-cited-olmo2 |
| PIQA | reasoning | 81.2 | instruct-cited-phi35moe |
| PIQA | reasoning | 78.9 | instruct-0-shot-cited-falcon3 |
| PIQA | reasoning | 45.8 | base-cited-marin |
| Winogrande | reasoning | 82.9 | base-cited-marin |
| Winogrande | reasoning | 76.6 | base-cited-olmo2 |
| Winogrande | reasoning | 64.7 | instruct-cited-phi35moe |
| TruthfulQA | safety | 69.2% | instruct-cited-phi35moe |
| TruthfulQA | safety | 55.1% | instruct-cited-tulu3 |
| TruthfulQA | safety | 52.79% | instruct-cited-granite-3-2 |
| TruthfulQA | safety | 44.29% | base-cited-falcon-mamba |
More models like Llama 3.1-8B
Frequently asked questions
What is Llama 3.1-8B? ▶
Llama 3.1-8B is an AI model developed by Meta AI, in the language category, released in 2024. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Llama 3.1-8B? ▶
Llama 3.1-8B was developed by Meta AI and released in 2024.
Is Llama 3.1-8B open source or proprietary? ▶
Llama 3.1-8B ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.
How much does Llama 3.1-8B cost? ▶
Pricing for Llama 3.1-8B depends on the provider. See the providers table on this page for the latest API rates.
How does Llama 3.1-8B perform on benchmarks? ▶
Llama 3.1-8B is benchmarked across 67 evaluations on GenAIList, including HumanEval (86.3%). See the full benchmark table below and compare it with other models.
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