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 vs Llama 3.1 405B
Model Overview
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.
Key Specifications
| Vendor | Release Date | Context Window | License |
|---|---|---|---|
| Google / Meta | 2024-02-15 / 2024-07-23 | 2000K / 128K | Proprietary / Llama 3 Community License |
Benchmark Performance
| Benchmark | Gemini 1.5 Pro | Llama 3.1 405B | Winner |
|---|---|---|---|
| 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 |
Pricing Comparison
| Input | Output | Cache Read | Cache Write |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
per million tokens — A / B
Strengths & Weaknesses
Gemini 1.5 Pro
- ✅ MMLU score 85.9, strong knowledge reasoning.
- ✅ GSM8K 91.7, robust math reasoning.
- ✅ Input Modalities: text, image, audio.
- ✅ Context window 2000K.
- ⚠️ Proprietary, not self-hostable.
Llama 3.1 405B
- ✅ MMLU score 88.6, strong knowledge reasoning.
- ✅ HumanEval 89.0, excellent code generation.
- ✅ GSM8K 89.2, robust math reasoning.
- ⚠️ Proprietary, not self-hostable.
Editor’s Take
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.
References
Editor's Take
See Editor's Take section.