Llama 3.2 3B vs Gemma 3 4B
Architecture Comparison
SpecLlama 3.2 3BGemma 3 4B
TypeDENSEDENSE
Total Parameters3.21B4.3B
Active Parameters3.21B4.3B
Layers2834
Hidden Dimension3,0722,560
Attention Heads2432
KV Heads88
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.2 3BGemma 3 4B
BF16 Weights6.4 GB8.6 GB
FP8 Weights3.2 GB4.3 GB
INT4 Weights1.6 GB2.1 GB
KV-Cache / Token114688 B139264 B
Activation Estimate0.50 GB0.50 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU1 GPU
L40S1 GPU1 GPU
Quality Benchmarks
BenchmarkLlama 3.2 3BGemma 3 4B
Overall5554
MMLU63.460.0
HumanEval33.032.0
GSM8K68.058.0
MT-Bench73.072.0
Llama 3.2 3B
MMLU
63.4
HumanEval
33.0
GSM8K
68.0
MT-Bench
73.0
Gemma 3 4B
MMLU
60.0
HumanEval
32.0
GSM8K
58.0
MT-Bench
72.0
Capabilities
FeatureLlama 3.2 3BGemma 3 4B
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 3.2 3B)
$0.06/M
Input: $0.06/M
Cheapest Output (Gemma 3 4B)
$0.10/M
Input: $0.05/M
| Provider | Llama 3.2 3B In $/M | Out $/M | Gemma 3 4B In $/M | Out $/M |
|---|---|---|---|---|
| together | $0.06 | $0.06 | — | — |
| fireworks | $0.10 | $0.10 | — | — |
| — | — | $0.05 | $0.10 |
Recommendation Summary
- ‣Llama 3.2 3B scores higher on overall quality (55 vs 54).
- ‣Llama 3.2 3B is cheaper per output token ($0.06/M vs $0.10/M).
- ‣Llama 3.2 3B has a smaller memory footprint (6.4 GB vs 8.6 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.2 3B is stronger at code generation (HumanEval: 33.0 vs 32.0).
- ‣Llama 3.2 3B is better at math reasoning (GSM8K: 68.0 vs 58.0).