Qwen 3 8B vs Llama 3.1 8B
Architecture Comparison
SpecQwen 3 8BLlama 3.1 8B
TypeDENSEDENSE
Total Parameters8.2B8.03B
Active Parameters8.2B8.03B
Layers3632
Hidden Dimension4,0964,096
Attention Heads3232
KV Heads88
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionQwen 3 8BLlama 3.1 8B
BF16 Weights16.4 GB16.1 GB
FP8 Weights8.2 GB8.0 GB
INT4 Weights4.1 GB4.0 GB
KV-Cache / Token147456 B131072 B
Activation Estimate1.00 GB1.00 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU1 GPU
L40S1 GPU1 GPU
Quality Benchmarks
BenchmarkQwen 3 8BLlama 3.1 8B
Overall6765
MMLU72.069.4
HumanEval42.040.2
GSM8K78.079.6
MT-Bench77.078.0
Qwen 3 8B
MMLU
72.0
HumanEval
42.0
GSM8K
78.0
MT-Bench
77.0
Llama 3.1 8B
MMLU
69.4
HumanEval
40.2
GSM8K
79.6
MT-Bench
78.0
Capabilities
FeatureQwen 3 8BLlama 3.1 8B
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✓ Yes✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Qwen 3 8B)
$0.20/M
Input: $0.20/M
Cheapest Output (Llama 3.1 8B)
$0.08/M
Input: $0.05/M
| Provider | Qwen 3 8B In $/M | Out $/M | Llama 3.1 8B In $/M | Out $/M |
|---|---|---|---|---|
| groq | — | — | $0.05 | $0.08 |
| together | $0.20 | $0.20 | $0.18 | $0.18 |
| fireworks | $0.20 | $0.20 | $0.20 | $0.20 |
Recommendation Summary
- ‣Qwen 3 8B scores higher on overall quality (67 vs 65).
- ‣Llama 3.1 8B is cheaper per output token ($0.08/M vs $0.20/M).
- ‣Llama 3.1 8B has a smaller memory footprint (16.1 GB vs 16.4 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Qwen 3 8B is stronger at code generation (HumanEval: 42.0 vs 40.2).
- ‣Llama 3.1 8B is better at math reasoning (GSM8K: 79.6 vs 78.0).