GPT-4o vs Llama 3.1 405B: Benchmark Comparison
Detailed comparison of GPT-4o and Llama 3.1 405B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | GPT-4o | Llama 3.1 405B |
|---|---|---|
| Vendor | openai | meta |
| Version | 4o | 3.1-405b |
| Release Date | 2024-05-13 | 2024-07-23 |
| Context Window | 128000 tokens | 128000 tokens |
| Input Modalities | text, image, audio | text |
| Output Modalities | text, audio | text |
| License | Proprietary | Llama 3 Community License |
| SOC2 | ✓ | ✗ |
| HIPAA | ✓ | ✗ |
| GDPR | ✓ | ✗ |
| ISO 27001 | ✓ | ✗ |
Benchmark Results
| Benchmark | GPT-4o | Llama 3.1 405B | Winner |
|---|---|---|---|
| BBH | 83.1 | 82.9 | GPT-4o |
| GSM8K | 95.8 | 89.2 | GPT-4o |
| HUMANEVAL | 90.2 | 89 | GPT-4o |
| MATH | 76.6 | 73.8 | GPT-4o |
| MMLU | 88.7 | 88.6 | GPT-4o |
Pricing Comparison
| Tier (per Mtok) | GPT-4o | Llama 3.1 405B |
|---|---|---|
| Input | $2.5 | $5 |
| Output | $10 | $15 |
| Cache Read | $1.25 | $0 |
| Cache Write | $2.5 | $0 |
GPT-4o contra Llama 3.1 405B
Descripción del modelo
GPT-4o and Llama 3.1 405B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Especificaciones clave
| Proveedor | Fecha de lanzamiento | Ventana de contexto | Licencia |
|---|---|---|---|
| Openai / Meta | 2024-05-13 / 2024-07-23 | 128K / 128K | Proprietary / Llama 3 Community License |
Rendimiento en benchmarks
| Benchmark | GPT-4o | Llama 3.1 405B | Ganador |
|---|---|---|---|
| BBH (BIG-Bench Hard) | 83.1 | 82.9 | Tie |
| GSM8K (Grade School Math 8K) | 95.8 | 89.2 | A |
| HumanEval | 90.2 | 89.0 | A |
| MATH | 76.6 | 73.8 | A |
| MMLU (Massive Multitask Language Understanding) | 88.7 | 88.6 | Tie |
Comparación de precios
| Entrada | Salida | Lectura caché | Escritura caché |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
por millón de tokens — A / B
Fortalezas & Debilidades
GPT-4o
- ✅ MMLU score 88.7, strong knowledge reasoning.
- ✅ HumanEval 90.2, excellent code generation.
- ✅ GSM8K 95.8, robust math reasoning.
- ✅ 支持文本、图像、音频多模态输入。
- ⚠️ 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。
Opinión del editor
GPT-4o and Llama 3.1 405B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
Preguntas frecuentes
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.
Referencias
Editor's Take
See Editor's Take section.