openai/whisper-large-v3
openai/whisper-large-v3
Whisper large-v3, state-of-the-art speech recognition.
Parameters
1.5B
Context
—
Downloads
4.1M
Likes
6.6K
Architecture
whisper
32 layers
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 9.5 GB RAM 32.0 · Disk 43.4 | 10.5 GB RAM 32.0 · Disk 69.4 | 12.2 GB RAM 32.0 · Disk 108.4 |
| FP88bit | 6.1 GB RAM 32.0 · Disk 41.2 | 7.0 GB RAM 32.0 · Disk 67.2 | 8.5 GB RAM 32.0 · Disk 106.2 |
| INT88bit | 6.1 GB RAM 32.0 · Disk 41.2 | 7.0 GB RAM 32.0 · Disk 67.2 | 8.5 GB RAM 32.0 · Disk 106.2 |
| AWQ4bit | 4.5 GB RAM 32.0 · Disk 40.1 | 5.3 GB RAM 32.0 · Disk 66.1 | 6.7 GB RAM 32.0 · Disk 105.1 |
| GPTQ4bit | 4.5 GB RAM 32.0 · Disk 40.1 | 5.3 GB RAM 32.0 · Disk 66.1 | 6.7 GB RAM 32.0 · Disk 105.1 |
| GGUF4bit | 4.6 GB RAM 32.0 · Disk 40.2 | 5.4 GB RAM 32.0 · Disk 66.2 | 6.8 GB RAM 32.0 · Disk 105.2 |
GPU Recommendations
1× RTX 3080 Ti
12 GB VRAM
≈ RTF 0.39
Effective production throughput ≈ 0.3 RTF
score 0.6122
1× Tesla V100
16 GB VRAM
≈ RTF 0 (N/A — benchmark unavailable)
Effective production throughput ≈ 0 RTF
score 0.5772
8× RTX 4090
192 GB VRAM
≈ RTF 0.11
Effective production throughput ≈ 0.1 RTF
score 0.3514
1× RTX 4060 Ti
8 GB VRAM
≈ RTF 1.22
Effective production throughput ≈ 0.9 RTF
score 0.6668
💬 Community — real deployment experience
0 Articles · 0 Benchmarks
GPUs that fit (single card)
Tesla V100
16 GB VRAM
$39.4
/mo · vast
RTX 4060 Ti
8 GB VRAM
$59.5
/mo · vast
RTX 4070S Ti
16 GB VRAM
$68.5
/mo · vast
RTX 3080
10 GB VRAM
$68.7
/mo · vast
RTX 5060 Ti
8 GB VRAM
$74.5
/mo · vast