Llama 3.3 70B vs Gemma 3 27B
Architecture Comparison
SpecLlama 3.3 70BGemma 3 27B
TypeDENSEDENSE
Total Parameters70.6B27B
Active Parameters70.6B27B
Layers8062
Hidden Dimension8,1923,584
Attention Heads6432
KV Heads816
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.3 70BGemma 3 27B
BF16 Weights141.2 GB54.0 GB
FP8 Weights70.6 GB27.0 GB
INT4 Weights35.3 GB13.5 GB
KV-Cache / Token327680 B507904 B
Activation Estimate2.50 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM3 GPUs1 GPU
L40S4 GPUs2 GPUs
Quality Benchmarks
BenchmarkLlama 3.3 70BGemma 3 27B
Overall8476
MMLU86.078.0
HumanEval60.048.0
GSM8K94.085.0
MT-Bench86.082.0
Llama 3.3 70B
MMLU
86.0
HumanEval
60.0
GSM8K
94.0
MT-Bench
86.0
Gemma 3 27B
MMLU
78.0
HumanEval
48.0
GSM8K
85.0
MT-Bench
82.0
Capabilities
FeatureLlama 3.3 70BGemma 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 3.3 70B)
$0.79/M
Input: $0.59/M
Cheapest Output (Gemma 3 27B)
$0.20/M
Input: $0.10/M
| Provider | Llama 3.3 70B In $/M | Out $/M | Gemma 3 27B In $/M | Out $/M |
|---|---|---|---|---|
| — | — | $0.10 | $0.20 | |
| together | $0.88 | $0.88 | $0.30 | $0.30 |
| groq | $0.59 | $0.79 | — | — |
| fireworks | $0.90 | $0.90 | — | — |
Recommendation Summary
- ‣Llama 3.3 70B scores higher on overall quality (84 vs 76).
- ‣Gemma 3 27B is cheaper per output token ($0.20/M vs $0.79/M).
- ‣Gemma 3 27B has a smaller memory footprint (54.0 GB vs 141.2 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.3 70B is stronger at code generation (HumanEval: 60.0 vs 48.0).
- ‣Llama 3.3 70B is better at math reasoning (GSM8K: 94.0 vs 85.0).