Qwen 2.5 7B vs Gemma 3 27B
Architecture Comparison
SpecQwen 2.5 7BGemma 3 27B
TypeDENSEDENSE
Total Parameters7.6B27B
Active Parameters7.6B27B
Layers2862
Hidden Dimension3,5843,584
Attention Heads2832
KV Heads416
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionQwen 2.5 7BGemma 3 27B
BF16 Weights15.2 GB54.0 GB
FP8 Weights7.6 GB27.0 GB
INT4 Weights3.8 GB13.5 GB
KV-Cache / Token57344 B507904 B
Activation Estimate1.00 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU1 GPU
L40S1 GPU2 GPUs
Quality Benchmarks
BenchmarkQwen 2.5 7BGemma 3 27B
Overall7076
MMLU74.278.0
HumanEval42.848.0
GSM8K82.085.0
MT-Bench79.082.0
Qwen 2.5 7B
MMLU
74.2
HumanEval
42.8
GSM8K
82.0
MT-Bench
79.0
Gemma 3 27B
MMLU
78.0
HumanEval
48.0
GSM8K
85.0
MT-Bench
82.0
Capabilities
FeatureQwen 2.5 7BGemma 3 27B
Tool Use✓ Yes✓ Yes
Vision✗ No✓ Yes
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Qwen 2.5 7B)
$0.20/M
Input: $0.20/M
Cheapest Output (Gemma 3 27B)
$0.20/M
Input: $0.10/M
| Provider | Qwen 2.5 7B In $/M | Out $/M | Gemma 3 27B In $/M | Out $/M |
|---|---|---|---|---|
| together | $0.20 | $0.20 | $0.30 | $0.30 |
| fireworks | $0.20 | $0.20 | — | — |
| — | — | $0.10 | $0.20 |
Recommendation Summary
- ‣Gemma 3 27B scores higher on overall quality (76 vs 70).
- ‣Qwen 2.5 7B has a smaller memory footprint (15.2 GB vs 54.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Gemma 3 27B is stronger at code generation (HumanEval: 48.0 vs 42.8).
- ‣Gemma 3 27B is better at math reasoning (GSM8K: 85.0 vs 82.0).