o1 vs Llama 3.1 405B: Benchmark Comparison
Detailed comparison of o1 and Llama 3.1 405B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | o1 | Llama 3.1 405B |
|---|---|---|
| Vendor | openai | meta |
| Version | o1 | 3.1-405b |
| Release Date | 2024-12-17 | 2024-07-23 |
| Context Window | 200000 tokens | 128000 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Proprietary | Llama 3 Community License |
| SOC2 | ✓ | ✗ |
| HIPAA | ✓ | ✗ |
| GDPR | ✓ | ✗ |
| ISO 27001 | ✓ | ✗ |
Benchmark Results
| Benchmark | o1 | Llama 3.1 405B | Winner |
|---|---|---|---|
| ARC | 96.8 | — | o1 |
| BBH | 83.1 | 82.9 | o1 |
| GPQA | 57.5 | — | o1 |
| GSM8K | 88.9 | 89.2 | Llama 3.1 405B |
| HUMANEVAL | 85.3 | 89 | Llama 3.1 405B |
| IFEVAL | 82.2 | — | o1 |
| MATH | 55.7 | 73.8 | Llama 3.1 405B |
| MMLU | 86.3 | 88.6 | Llama 3.1 405B |
| MUSR | 71.8 | — | o1 |
| WINOGRANDE | 86.7 | — | o1 |
Pricing Comparison
| Tier (per Mtok) | o1 | Llama 3.1 405B |
|---|---|---|
| Input | $15 | $5 |
| Output | $60 | $15 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
o1 contra Llama 3.1 405B
Visão geral do modelo
o1 and Llama 3.1 405B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Especificações principais
| Fornecedor | Data de lançamento | Janela de contexto | Licença |
|---|---|---|---|
| Openai / Meta | 2024-12-17 / 2024-07-23 | 200K / 128K | Proprietary / Llama 3 Community License |
Desempenho em benchmarks
| Benchmark | o1 | Llama 3.1 405B | Vencedor |
|---|---|---|---|
| ARC | 96.8 | — | A |
| BBH (BIG-Bench Hard) | 83.1 | 82.9 | Tie |
| GPQA | 57.5 | — | A |
| GSM8K (Grade School Math 8K) | 88.9 | 89.2 | Tie |
| HumanEval | 85.3 | 89.0 | B |
| IFEval | 82.2 | — | A |
| MATH | 55.7 | 73.8 | B |
| MMLU (Massive Multitask Language Understanding) | 86.3 | 88.6 | B |
| MUSR | 71.8 | — | A |
| WinoGrande | 86.7 | — | A |
Comparação de preços
| Entrada | Saída | Leitura de cache | Escrita de cache |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
por milhão de tokens — A / B
Pontos fortes & Pontos fracos
o1
- ✅ MMLU score 86.3, strong knowledge reasoning.
- ✅ HumanEval 85.3, excellent code generation.
- ✅ GSM8K 88.9, robust math reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
Llama 3.1 405B
- ✅ MMLU score 88.6, strong knowledge reasoning.
- ✅ HumanEval 89.0, excellent code generation.
- ✅ GSM8K 89.2, robust math reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
Opinião do editor
o1 and Llama 3.1 405B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
Perguntas frequentes
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
Referências
Editor's Take
See Editor's Take section.