Llama 3.1 8B vs Qwen2.5 7B: Benchmark Comparison
Detailed comparison of Llama 3.1 8B and Qwen2.5 7B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Llama 3.1 8B | Qwen2.5 7B |
|---|---|---|
| Vendor | meta | alibaba |
| Version | 3.1-8b | 2.5-7b |
| Release Date | 2024-07-23 | 2024-09-19 |
| Context Window | 128000 tokens | 131072 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Llama 3 Community License | Qwen License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | Llama 3.1 8B | Qwen2.5 7B | Winner |
|---|---|---|---|
| ARC | 87.4 | 88.4 | Qwen2.5 7B |
| BBH | 67.1 | 61.9 | Llama 3.1 8B |
| GPQA | 34.8 | 28.5 | Llama 3.1 8B |
| GSM8K | 58.8 | 63.7 | Qwen2.5 7B |
| HUMANEVAL | 63.4 | 66.5 | Qwen2.5 7B |
| IFEVAL | 62.1 | 55.4 | Llama 3.1 8B |
| MATH | 31.1 | 41.9 | Qwen2.5 7B |
| MMLU | 73 | 73.6 | Qwen2.5 7B |
| MUSR | 41.7 | 46.9 | Qwen2.5 7B |
| WINOGRANDE | 77.6 | 71.4 | Llama 3.1 8B |
Pricing Comparison
| Tier (per Mtok) | Llama 3.1 8B | Qwen2.5 7B |
|---|---|---|
| Input | $0.18 | $0.15 |
| Output | $0.18 | $0.15 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
Llama 3.1 8B 対 Qwen2.5 7B
モデル概要
Llama 3.1 8B and Qwen2.5 7B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
主要仕様
| ベンダー | リリース日 | コンテキストウィンドウ | ライセンス |
|---|---|---|---|
| Meta / Alibaba | 2024-07-23 / 2024-09-19 | 128K / 131K | Llama 3 Community License / Qwen License |
ベンチマークパフォーマンス
| ベンチマーク | Llama 3.1 8B | Qwen2.5 7B | 勝者 |
|---|---|---|---|
| ARC | 87.4 | 88.4 | B |
| BBH (BIG-Bench Hard) | 67.1 | 61.9 | A |
| GPQA | 34.8 | 28.5 | A |
| GSM8K (Grade School Math 8K) | 58.8 | 63.7 | B |
| HumanEval | 63.4 | 66.5 | B |
| IFEval | 62.1 | 55.4 | A |
| MATH | 31.1 | 41.9 | B |
| MMLU (Massive Multitask Language Understanding) | 73.0 | 73.6 | B |
| MUSR | 41.7 | 46.9 | B |
| WinoGrande | 77.6 | 71.4 | A |
料金比較
| 入力 | 出力 | キャッシュ読み取り | キャッシュ書き込み |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
100万トークンあたり — A / B
強み & 弱み
Llama 3.1 8B
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
Qwen2.5 7B
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
編集者コメント
Llama 3.1 8B and Qwen2.5 7B 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.
参考文献
Editor's Take
See Editor's Take section.