meta-llama/Llama-3.2-1B-Instruct
meta-llama/Llama-3.2-1B-Instruct
Parameters
1B
Context
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Downloads
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Architecture
—
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 7.3 GB RAM 32.0 · Disk 41.9 | 23.2 GB RAM 34.8 · Disk 67.9 | 120.2 GB RAM 180.3 · Disk 106.9 |
| FP88bit | 6.1 GB RAM 32.0 · Disk 40.5 | 21.9 GB RAM 32.9 · Disk 66.5 | 118.9 GB RAM 178.3 · Disk 105.5 |
| INT88bit | 6.1 GB RAM 32.0 · Disk 40.5 | 21.9 GB RAM 32.9 · Disk 66.5 | 118.9 GB RAM 178.3 · Disk 105.5 |
| AWQ4bit | 5.6 GB RAM 32.0 · Disk 39.8 | 21.3 GB RAM 32.0 · Disk 65.8 | 118.3 GB RAM 177.4 · Disk 104.8 |
| GPTQ4bit | 5.6 GB RAM 32.0 · Disk 39.8 | 21.4 GB RAM 32.0 · Disk 65.8 | 118.3 GB RAM 177.4 · Disk 104.8 |
| GGUF4bit | 5.6 GB RAM 32.0 · Disk 39.8 | 21.4 GB RAM 32.0 · Disk 65.8 | 118.3 GB RAM 177.4 · Disk 104.8 |
GPU Recommendations
1× RTX 5090
32 GB VRAM
≈ 3733.3 tok/s
Effective production throughput ≈ 2613.3 tok/s
score 0.6745
2× Tesla V100
32 GB VRAM
≈ 0 tok/s (N/A — benchmark unavailable)
Effective production throughput ≈ 0 tok/s
score 0.6238
8× H200 SXM
1128 GB VRAM
≈ 32000 tok/s
Effective production throughput ≈ 22400 tok/s
score 0.2197
1× L4
24 GB VRAM
≈ 625 tok/s
Effective production throughput ≈ 437.5 tok/s
score 0.6534
💬 Community — real deployment experience
0 Articles · 0 Benchmarks
GPUs that fit (single card)
L4
24 GB VRAM
$76.2
/mo · vast
RTX 3090
24 GB VRAM
$79.6
/mo · vast
RTX 4090
24 GB VRAM
$190
/mo · tensordock
A100 SXM4
80 GB VRAM
$225
/mo · vast
RTX 5090
32 GB VRAM
$293
/mo · vast