Gemini 1.5 Pro vs Llama 3.1 405B: Benchmark Comparison
Detailed comparison of Gemini 1.5 Pro and Llama 3.1 405B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Gemini 1.5 Pro | Llama 3.1 405B |
|---|---|---|
| Vendor | meta | |
| Version | 1.5-pro | 3.1-405b |
| Release Date | 2024-02-15 | 2024-07-23 |
| Context Window | 2e+06 tokens | 128000 tokens |
| Input Modalities | text, image, audio, video | text |
| Output Modalities | text | text |
| License | Proprietary | Llama 3 Community License |
| SOC2 | ✓ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✓ | ✗ |
| ISO 27001 | ✓ | ✗ |
Benchmark Results
| Benchmark | Gemini 1.5 Pro | Llama 3.1 405B | Winner |
|---|---|---|---|
| BBH | 84 | 82.9 | Gemini 1.5 Pro |
| GSM8K | 91.7 | 89.2 | Gemini 1.5 Pro |
| HUMANEVAL | 71.9 | 89 | Llama 3.1 405B |
| MATH | 58.5 | 73.8 | Llama 3.1 405B |
| MMLU | 85.9 | 88.6 | Llama 3.1 405B |
Pricing Comparison
| Tier (per Mtok) | Gemini 1.5 Pro | Llama 3.1 405B |
|---|---|---|
| Input | $1.25 | $5 |
| Output | $5 | $15 |
| Cache Read | $0.3125 | $0 |
| Cache Write | $1.25 | $0 |
Gemini 1.5 Pro contro Llama 3.1 405B
Panoramica del modello
Gemini 1.5 Pro and Llama 3.1 405B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Specifiche chiave
| Fornitore | Data di rilascio | Finestra di contesto | Licenza |
|---|---|---|---|
| Google / Meta | 2024-02-15 / 2024-07-23 | 2000K / 128K | Proprietary / Llama 3 Community License |
Prestazioni benchmark
| Benchmark | Gemini 1.5 Pro | Llama 3.1 405B | Vincitore |
|---|---|---|---|
| BBH (BIG-Bench Hard) | 84.0 | 82.9 | A |
| GSM8K (Grade School Math 8K) | 91.7 | 89.2 | A |
| HumanEval | 71.9 | 89.0 | B |
| MATH | 58.5 | 73.8 | B |
| MMLU (Massive Multitask Language Understanding) | 85.9 | 88.6 | B |
Confronto prezzi
| Input | Output | Lettura cache | Scrittura cache |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
per milione di token — A / B
Punti di forza & Punti deboli
Gemini 1.5 Pro
- ✅ MMLU score 85.9, strong knowledge reasoning.
- ✅ GSM8K 91.7, robust math reasoning.
- ✅ 支持文本、图像、音频多模态输入。
- ✅ 上下文窗口 2000K，支持长文本。
- ⚠️ 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。
Opinione dell’editore
Gemini 1.5 Pro and Llama 3.1 405B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
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.
Riferimenti
Editor's Take
See Editor's Take section.