Updated minutes ago
RecurrentGemma 2B
Google · dense · 2.7B parameters · 8,192 context
Quality50.0
Architecture Details
TypeDENSE
Total Parameters2.7B
Active Parameters2.7B
Layers26
Hidden Dimension2,560
Attention Heads10
KV Heads1
Head Dimension256
Vocab Size256,000
Memory Requirements
BF16 Weights
5.4 GB
FP8 Weights
2.7 GB
INT4 Weights
1.4 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 3080optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
684.0 tok/s
Cost/Month
$133
Cost/M Tokens
$0.07
RTX 4060optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
244.8 tok/s
Cost/Month
$209
Cost/M Tokens
$0.32
RTX 3070optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
403.2 tok/s
Cost/Month
$85
Cost/M Tokens
$0.08
API Pricing Comparison
No API pricing data available for this model.
Capabilities
Features
✗ Tool Use✗ Vision✗ Code✗ Math✗ Reasoning✓ Multilingual✗ Structured Output
Supported Frameworks
vllmsglang
Supported Precisions
BF16 (default)FP8INT4