MedGemma 1.5 4B
google/medgemma-1.5-4b-it
Parameters
4.3B
Context
128K
Downloads
315.8K
Likes
776
Architecture
transformer
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 13.7 GB RAM 32.0 · Disk 51.5 | 16.3 GB RAM 32.0 · Disk 77.5 | 32.7 GB RAM 49.0 · Disk 116.5 |
| FP88bit | 8.6 GB RAM 32.0 · Disk 45.3 | 11.1 GB RAM 32.0 · Disk 71.3 | 27.1 GB RAM 40.7 · Disk 110.3 |
| INT88bit | 8.6 GB RAM 32.0 · Disk 45.3 | 11.1 GB RAM 32.0 · Disk 71.3 | 27.1 GB RAM 40.7 · Disk 110.3 |
| AWQ4bit | 6.2 GB RAM 32.0 · Disk 42.2 | 8.5 GB RAM 32.0 · Disk 68.2 | 24.5 GB RAM 36.7 · Disk 107.2 |
| GPTQ4bit | 6.2 GB RAM 32.0 · Disk 42.3 | 8.5 GB RAM 32.0 · Disk 68.3 | 24.5 GB RAM 36.8 · Disk 107.3 |
| GGUF4bit | 6.3 GB RAM 32.0 · Disk 42.4 | 8.6 GB RAM 32.0 · Disk 68.4 | 24.6 GB RAM 36.9 · Disk 107.4 |
GPU Recommendations
1× RTX 5080
16 GB VRAM
≈ 461.5 tok/s
Effective production throughput ≈ 323 tok/s
score 0.6366
1× Tesla V100
16 GB VRAM
≈ 0 tok/s (N/A — benchmark unavailable)
Effective production throughput ≈ 0 tok/s
score 0.6312
8× RTX 5090
256 GB VRAM
≈ 2756.9 tok/s
Effective production throughput ≈ 1929.8 tok/s
score 0.3617
1× RTX 5070
12 GB VRAM
≈ 323.1 tok/s
Effective production throughput ≈ 226.2 tok/s
score 0.6825
💬 Community — real deployment experience
0 Articles · 0 Benchmarks
GPUs that fit (single card)
Tesla V100
16 GB VRAM
$20.3
/mo · vast
RTX 4070S Ti
16 GB VRAM
$49.5
/mo · vast
RTX 4080S
16 GB VRAM
$50.0
/mo · vast
RTX 5070
12 GB VRAM
$58.7
/mo · vast
RTX 5070 Ti
16 GB VRAM
$62.0
/mo · vast