Open-weight LLM comparison
Llama 3.1 8B vs Qwen 2.5 7B
Side-by-side
Straight from each model's release page and Hugging Face card. Memory shown is for the weights alone: add roughly 15% for real serving. Bold column marks the more parameters and the smaller memory footprint.
| Field | Llama 3.1 8B | Qwen 2.5 7B |
|---|---|---|
| Total parameters | 8 B | 7 B |
| Architecture | dense | dense |
| Vendor | Meta | Alibaba |
| License | Llama 3.1 Community License | Apache 2.0 |
| Released | 2024-07-23 | 2024-09-19 |
| Weights @ FP16 | 16 GB | 14 GB |
| Weights @ INT8 | 8 GB | 7 GB |
| Weights @ INT4 | 4 GB | 4 GB |
Which is smarter (published benchmarks)
Vendor-reported quality scores on the standard leaderboards. Bold column marks the higher score on the same test.
| Benchmark | Llama 3.1 8B | Qwen 2.5 7B |
|---|---|---|
| MMLU (5-shot) | 73.0 | 74.2 |
| HumanEval | 72.6 | 84.8 |
| MATH (0-shot) | 51.9 | 75.5 |
| GPQA | 32.8 | not published |
Sources: Llama 3.1 8B model card · Qwen 2.5 7B model card. Benchmark methodology and prompt template can shift these numbers by several points, so treat these as relative rankings, not absolute scores.
Common questions
Llama 3.1 8B vs Qwen 2.5 7B: which is bigger?
Llama 3.1 8B has more parameters (Llama 3.1 8B: 8 B; Qwen 2.5 7B: 7 B). More parameters usually means higher ceiling on capability and higher memory requirement, though MoE architectures decouple total parameters from per-token compute.
Llama 3.1 8B vs Qwen 2.5 7B: which is newer?
Qwen 2.5 7B released 2024-09-19; Llama 3.1 8B released 2024-07-23.
Llama 3.1 8B vs Qwen 2.5 7B: which needs less memory to serve?
Qwen 2.5 7B needs less HBM. Weights-only footprint at FP16: Llama 3.1 8B 16 GB; Qwen 2.5 7B 14 GB. Half those numbers at INT8, quarter at INT4. Real serving adds 10-30% for KV cache.
Llama 3.1 8B vs Qwen 2.5 7B: which license is more permissive?
Llama 3.1 8B: Llama 3.1 Community License. Qwen 2.5 7B: Apache 2.0. Apache 2.0 and MIT allow unrestricted commercial use; Llama Community License allows commercial use but restricts training larger models on outputs; CC-BY-NC and vendor-specific licenses (Qwen 72B, Gemma) have narrower terms. Check the model card for the exact clauses.
See also: every LLM comparison · Llama 3.1 8B full page · Qwen 2.5 7B full page.