Updated minutes ago
Gemma 3 2B
Google · dense · 2B parameters · 8,192 context
Quality42.0
Architecture Details
TypeDENSE
Total Parameters2B
Active Parameters2B
Layers26
Hidden Dimension2,304
Attention Heads8
KV Heads4
Head Dimension256
Vocab Size262,144
Memory Requirements
BF16 Weights
4.0 GB
FP8 Weights
2.0 GB
INT4 Weights
1.0 GB
KV-Cache per Token26624 bytes
Activation Estimate0.30 GB
Fits on (single-node)
B200 SXM BF16B100 SXM BF16GB200 NVL72 (per GPU) BF16GB300 NVL72 (per GPU) BF16H200 SXM BF16H100 SXM BF16H100 PCIe BF16H100 NVL BF16
GPU Recommendations
RTX 4060optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
330.5 tok/s
Cost/Month
$209
Cost/M Tokens
$0.24
RTX 3070optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
544.3 tok/s
Cost/Month
$85
Cost/M Tokens
$0.06
A4000optimal
BF16 · 1 GPU · vllm
90/100
score
Throughput
544.3 tok/s
Cost/Month
$161
Cost/M Tokens
$0.11
API Pricing Comparison
No API pricing data available for this model.
Quality Benchmarks
MMLU50.0
HumanEval22.0
GSM8K42.0
MT-Bench65.0
Capabilities
Features
✗ Tool Use✗ Vision✓ Code✓ Math✗ Reasoning✓ Multilingual✓ Structured Output
Supported Frameworks
vllmsglangtgiollama
Supported Precisions
BF16 (default)FP8INT4