Llama 3.1 405B vs DeepSeek V3: Benchmark Comparison
Detailed comparison of Llama 3.1 405B and DeepSeek V3 covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Llama 3.1 405B | DeepSeek V3 |
|---|---|---|
| Vendor | meta | deepseek |
| Version | 3.1-405b | v3 |
| Release Date | 2024-07-23 | 2024-12-26 |
| Context Window | 128000 tokens | 64000 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Llama 3 Community License | DeepSeek License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | Llama 3.1 405B | DeepSeek V3 | Winner |
|---|---|---|---|
| BBH | 82.9 | 84.9 | DeepSeek V3 |
| GSM8K | 89.2 | 89.3 | DeepSeek V3 |
| HUMANEVAL | 89 | 82.6 | Llama 3.1 405B |
| MATH | 73.8 | 61.6 | Llama 3.1 405B |
| MMLU | 88.6 | 88.5 | Llama 3.1 405B |
Pricing Comparison
| Tier (per Mtok) | Llama 3.1 405B | DeepSeek V3 |
|---|---|---|
| Input | $5 | $0.27 |
| Output | $15 | $1.1 |
| Cache Read | $0 | $0.07 |
| Cache Write | $0 | $0.27 |
Llama 3.1 405B contra DeepSeek V3
Descripción del modelo
Llama 3.1 405B and DeepSeek V3 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 |
|---|---|---|---|
| Meta / Deepseek | 2024-07-23 / 2024-12-26 | 128K / 64K | Llama 3 Community License / DeepSeek License |
Rendimiento en benchmarks
| Benchmark | Llama 3.1 405B | DeepSeek V3 | Ganador |
|---|---|---|---|
| BBH (BIG-Bench Hard) | 82.9 | 84.9 | B |
| GSM8K (Grade School Math 8K) | 89.2 | 89.3 | Tie |
| HumanEval | 89.0 | 82.6 | A |
| MATH | 73.8 | 61.6 | A |
| MMLU (Massive Multitask Language Understanding) | 88.6 | 88.5 | Tie |
Comparación de precios
| Entrada | Salida | Lectura caché | Escritura caché |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
por millón de tokens — A / B
Fortalezas & Debilidades
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。
DeepSeek V3
- ✅ MMLU score 88.5, strong knowledge reasoning.
- ✅ HumanEval 82.6, excellent code generation.
- ✅ GSM8K 89.3, robust math reasoning.
- ✅ 采用 MoE 混合专家架构。
- ⚠️ 闭源专有模型，不支持自托管。
Opinión del editor
Llama 3.1 405B and DeepSeek V3 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.