Gemma 3 27B vs Llama 3.1 405B
Architecture Comparison
SpecGemma 3 27BLlama 3.1 405B
TypeDENSEDENSE
Total Parameters27B405B
Active Parameters27B405B
Layers62126
Hidden Dimension3,58416,384
Attention Heads32128
KV Heads168
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionGemma 3 27BLlama 3.1 405B
BF16 Weights54.0 GB810.0 GB
FP8 Weights27.0 GB405.0 GB
INT4 Weights13.5 GB202.5 GB
KV-Cache / Token507904 B516096 B
Activation Estimate1.50 GB5.00 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPUN/A
L40S2 GPUsN/A
Quality Benchmarks
BenchmarkGemma 3 27BLlama 3.1 405B
Overall7688
MMLU78.088.6
HumanEval48.061.0
GSM8K85.096.8
MT-Bench82.088.0
Gemma 3 27B
MMLU
78.0
HumanEval
48.0
GSM8K
85.0
MT-Bench
82.0
Llama 3.1 405B
MMLU
88.6
HumanEval
61.0
GSM8K
96.8
MT-Bench
88.0
Capabilities
FeatureGemma 3 27BLlama 3.1 405B
Tool Use✓ Yes✓ Yes
Vision✓ Yes✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Gemma 3 27B)
$0.20/M
Input: $0.10/M
Cheapest Output (Llama 3.1 405B)
$3.00/M
Input: $3.00/M
| Provider | Gemma 3 27B In $/M | Out $/M | Llama 3.1 405B In $/M | Out $/M |
|---|---|---|---|---|
| $0.10 | $0.20 | — | — | |
| together | $0.30 | $0.30 | $3.50 | $3.50 |
| fireworks | — | — | $3.00 | $3.00 |
Recommendation Summary
- ‣Llama 3.1 405B scores higher on overall quality (88 vs 76).
- ‣Gemma 3 27B is cheaper per output token ($0.20/M vs $3.00/M).
- ‣Gemma 3 27B has a smaller memory footprint (54.0 GB vs 810.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 405B is stronger at code generation (HumanEval: 61.0 vs 48.0).
- ‣Llama 3.1 405B is better at math reasoning (GSM8K: 96.8 vs 85.0).