DeepSeek V3 vs Gemma 3 27B
Architecture Comparison
SpecDeepSeek V3Gemma 3 27B
TypeMOEDENSE
Total Parameters671B27B
Active Parameters37B27B
Layers6162
Hidden Dimension7,1683,584
Attention Heads12832
KV Heads116
Context Length131,072131,072
Precision (default)BF16BF16
Total Experts256N/A
Active Experts8N/A
Memory Requirements
PrecisionDeepSeek V3Gemma 3 27B
BF16 Weights1342.0 GB54.0 GB
FP8 Weights671.0 GB27.0 GB
INT4 Weights335.5 GB13.5 GB
KV-Cache / Token31232 B507904 B
Activation Estimate3.00 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXMN/A1 GPU
L40SN/A2 GPUs
Quality Benchmarks
BenchmarkDeepSeek V3Gemma 3 27B
Overall8676
MMLU87.178.0
HumanEval65.048.0
GSM8K89.385.0
MT-Bench87.082.0
DeepSeek V3
MMLU
87.1
HumanEval
65.0
GSM8K
89.3
MT-Bench
87.0
Gemma 3 27B
MMLU
78.0
HumanEval
48.0
GSM8K
85.0
MT-Bench
82.0
Capabilities
FeatureDeepSeek V3Gemma 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 (DeepSeek V3)
$0.42/M
Input: $0.28/M
Cheapest Output (Gemma 3 27B)
$0.20/M
Input: $0.10/M
| Provider | DeepSeek V3 In $/M | Out $/M | Gemma 3 27B In $/M | Out $/M |
|---|---|---|---|---|
| — | — | $0.10 | $0.20 | |
| together | $0.50 | $2.80 | $0.30 | $0.30 |
| deepseek | $0.28 | $0.42 | — | — |
Recommendation Summary
- ‣DeepSeek V3 scores higher on overall quality (86 vs 76).
- ‣Gemma 3 27B is cheaper per output token ($0.20/M vs $0.42/M).
- ‣Gemma 3 27B has a smaller memory footprint (54.0 GB vs 1342.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣DeepSeek V3 uses MOE architecture while Gemma 3 27B uses DENSE. MoE models activate fewer parameters per token, improving inference efficiency.
- ‣DeepSeek V3 is stronger at code generation (HumanEval: 65.0 vs 48.0).
- ‣DeepSeek V3 is better at math reasoning (GSM8K: 89.3 vs 85.0).