Llama 3.1 8B vs Mistral 7B v0.3: Benchmark Comparison
Detailed comparison of Llama 3.1 8B and Mistral 7B v0.3 covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Llama 3.1 8B | Mistral 7B v0.3 |
|---|---|---|
| Vendor | meta | mistral |
| Version | 3.1-8b | 7b-v0.3 |
| Release Date | 2024-07-23 | 2024-05-22 |
| Context Window | 128000 tokens | 32768 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Llama 3 Community License | Apache 2.0 |
| SOC2 | ✗ | ✓ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✓ |
| ISO 27001 | ✗ | ✓ |
Benchmark Results
| Benchmark | Llama 3.1 8B | Mistral 7B v0.3 | Winner |
|---|---|---|---|
| ARC | 87.4 | 88.9 | Mistral 7B v0.3 |
| BBH | 67.1 | 60.5 | Llama 3.1 8B |
| GPQA | 34.8 | 31.2 | Llama 3.1 8B |
| GSM8K | 58.8 | 69.4 | Mistral 7B v0.3 |
| HUMANEVAL | 63.4 | 68.8 | Mistral 7B v0.3 |
| IFEVAL | 62.1 | 60.9 | Llama 3.1 8B |
| MATH | 31.1 | 26.7 | Llama 3.1 8B |
| MMLU | 73 | 72.6 | Llama 3.1 8B |
| MUSR | 41.7 | 48.1 | Mistral 7B v0.3 |
| WINOGRANDE | 77.6 | 72.7 | Llama 3.1 8B |
Pricing Comparison
| Tier (per Mtok) | Llama 3.1 8B | Mistral 7B v0.3 |
|---|---|---|
| Input | $0.18 | $0.18 |
| Output | $0.18 | $0.18 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
Llama 3.1 8B karşı Mistral 7B v0.3
Model Genel Bakışı
Llama 3.1 8B and Mistral 7B v0.3 are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Temel Özellikler
| Satıcı | Yayın Tarihi | Bağlam Penceresi | Lisans |
|---|---|---|---|
| Meta / Mistral | 2024-07-23 / 2024-05-22 | 128K / 32K | Llama 3 Community License / Apache 2.0 |
Benchmark Performansı
| Benchmark | Llama 3.1 8B | Mistral 7B v0.3 | Kazanan |
|---|---|---|---|
| ARC | 87.4 | 88.9 | B |
| BBH (BIG-Bench Hard) | 67.1 | 60.5 | A |
| GPQA | 34.8 | 31.2 | A |
| GSM8K (Grade School Math 8K) | 58.8 | 69.4 | B |
| HumanEval | 63.4 | 68.8 | B |
| IFEval | 62.1 | 60.9 | A |
| MATH | 31.1 | 26.7 | A |
| MMLU (Massive Multitask Language Understanding) | 73.0 | 72.6 | Tie |
| MUSR | 41.7 | 48.1 | B |
| WinoGrande | 77.6 | 72.7 | A |
Fiyat Karşılaştırması
| Giriş | Çıkış | Önbellek Okuma | Önbellek Yazma |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
milyon token başına — A / B
Güçlü Yönler & Zayıf Yönler
Llama 3.1 8B
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
Mistral 7B v0.3
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
Editör Görüşü
Llama 3.1 8B and Mistral 7B v0.3 each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
SSS
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.
Referanslar
Editor's Take
See Editor's Take section.