Llama 3.1 8B vs Gemma 3 27B
Architecture Comparison
SpecLlama 3.1 8BGemma 3 27B
TypeDENSEDENSE
Total Parameters8.03B27B
Active Parameters8.03B27B
Layers3262
Hidden Dimension4,0963,584
Attention Heads3232
KV Heads816
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.1 8BGemma 3 27B
BF16 Weights16.1 GB54.0 GB
FP8 Weights8.0 GB27.0 GB
INT4 Weights4.0 GB13.5 GB
KV-Cache / Token131072 B507904 B
Activation Estimate1.00 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU1 GPU
L40S1 GPU2 GPUs
Quality Benchmarks
BenchmarkLlama 3.1 8BGemma 3 27B
Overall6576
MMLU69.478.0
HumanEval40.248.0
GSM8K79.685.0
MT-Bench78.082.0
Llama 3.1 8B
MMLU
69.4
HumanEval
40.2
GSM8K
79.6
MT-Bench
78.0
Gemma 3 27B
MMLU
78.0
HumanEval
48.0
GSM8K
85.0
MT-Bench
82.0
Capabilities
FeatureLlama 3.1 8BGemma 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 (Llama 3.1 8B)
$0.08/M
Input: $0.05/M
Cheapest Output (Gemma 3 27B)
$0.20/M
Input: $0.10/M
| Provider | Llama 3.1 8B In $/M | Out $/M | Gemma 3 27B In $/M | Out $/M |
|---|---|---|---|---|
| groq | $0.05 | $0.08 | — | — |
| together | $0.18 | $0.18 | $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 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 54.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Gemma 3 27B is stronger at code generation (HumanEval: 48.0 vs 40.2).
- ‣Gemma 3 27B is better at math reasoning (GSM8K: 85.0 vs 79.6).