Llama 3.1 70B vs Qwen2.5 72B: Benchmark Comparison
Detailed comparison of Llama 3.1 70B and Qwen2.5 72B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Llama 3.1 70B | Qwen2.5 72B |
|---|---|---|
| Vendor | meta | alibaba |
| Version | 3.1-70b | 2.5-72b |
| 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 70B | Qwen2.5 72B | Winner |
|---|---|---|---|
| ARC | 92.3 | — | Llama 3.1 70B |
| BBH | 70.2 | 82.4 | Qwen2.5 72B |
| GPQA | 40 | — | Llama 3.1 70B |
| GSM8K | 78.8 | 88.4 | Qwen2.5 72B |
| HUMANEVAL | 79.7 | 86.6 | Qwen2.5 72B |
| IFEVAL | 73.7 | — | Llama 3.1 70B |
| MATH | 38.5 | 83.1 | Qwen2.5 72B |
| MMLU | 75.6 | 86.1 | Qwen2.5 72B |
| MUSR | 48.1 | — | Llama 3.1 70B |
| WINOGRANDE | 81 | — | Llama 3.1 70B |
Pricing Comparison
| Tier (per Mtok) | Llama 3.1 70B | Qwen2.5 72B |
|---|---|---|
| Input | $0.9 | $0.5 |
| Output | $0.9 | $0.8 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
Llama 3.1 70B vs Qwen2.5 72B
Model Overview
Llama 3.1 70B and Qwen2.5 72B 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 |
|---|---|---|---|
| Meta / Alibaba | 2024-07-23 / 2024-09-19 | 128K / 131K | Llama 3 Community License / Qwen License |
Benchmark Performance
| Benchmark | Llama 3.1 70B | Qwen2.5 72B | Winner |
|---|---|---|---|
| ARC | 92.3 | — | A |
| BBH (BIG-Bench Hard) | 70.2 | 82.4 | B |
| GPQA | 40.0 | — | A |
| GSM8K (Grade School Math 8K) | 78.8 | 88.4 | B |
| HumanEval | 79.7 | 86.6 | B |
| IFEval | 73.7 | — | A |
| MATH | 38.5 | 83.1 | B |
| MMLU (Massive Multitask Language Understanding) | 75.6 | 86.1 | B |
| MUSR | 48.1 | — | A |
| WinoGrande | 81.0 | — | A |
Pricing Comparison
| Input | Output | Cache Read | Cache Write |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
per million tokens — A / B
Strengths & Weaknesses
Llama 3.1 70B
- ✅ Reliable general-purpose model.
- ⚠️ Proprietary, not self-hostable.
Qwen2.5 72B
- ✅ MMLU score 86.1, strong knowledge reasoning.
- ✅ HumanEval 86.6, excellent code generation.
- ✅ GSM8K 88.4, robust math reasoning.
- ⚠️ Proprietary, not self-hostable.
Editor’s Take
Llama 3.1 70B and Qwen2.5 72B 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.