Can the GeForce RTX 5090 run Whisper large-v3?
Whisper large-v3 runs locally on almost any modern GPU: the 1.54-billion-parameter model needs about 4.4 GB of VRAM at FP16 and about 2.2 GB at Q5, including runtime overhead. A 6 GB GPU transcribes in real time, and even CPU-only inference is practical at roughly real-time speed with whisper.cpp.
At Q4_K_M quantization with 32,768 context, the Whisper large-v3 requires approximately 2.01GB of VRAM. The GeForce RTX 5090 has 32GB available (29.99GB headroom).
VRAM Breakdown
| Component | Size (GB) | Source |
|---|---|---|
| Model weights (Q4_K_M) | 0.92 | calculated |
| Loading overhead (10%) | 0.09 | calculated |
| Activation overhead | 1.0 | vendor_spec |
| Total required | 2.01 | |
| GPU memory available | 32 | vendor_spec |
| Headroom / shortfall | +29.99 |
Quantization Options
| Quant | Weights (GB) | Total @ 4K (GB) | Total @ 32K (GB) | Fits GeForce RTX 5090? |
|---|---|---|---|---|
| Q4_K_M | 0.92 | 2.01 | 2.01 | Yes |
| Q5_K_M | 1.1 | 2.21 | 2.21 | Yes |
| Q6_K | 1.27 | 2.4 | 2.4 | Yes |
| Q8_0 | 1.64 | 2.8 | 2.8 | Yes |
| FP16 | 3.08 | 4.39 | 4.39 | Yes |
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If It Doesn't Fit: Alternatives
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Frequently Asked Questions
Can the Whisper large-v3 run on 32GB VRAM?
Yes. At Q4_K_M quantization with 4K context, the Whisper large-v3 needs approximately 2.01GB. Your 32GB of usable memory has 29.99GB headroom.
What is the maximum context length I can use on the GeForce RTX 5090?
The Whisper large-v3 supports up to 32,768 tokens of context. Larger context increases KV-cache memory requirements. At 4K context the model needs ~2.01GB; at 32K it needs more.
Which quantization should I use with the GeForce RTX 5090?
Q4_K_M is the recommended starting point — it offers the best speed-to-quality tradeoff. If you have VRAM headroom, Q6_K or Q8_0 improves quality at the cost of speed. FP16 is only for inference servers with ample memory.
How much VRAM does Whisper large-v3 need?
Whisper large-v3 needs about 4.4 GB of VRAM at FP16 and about 2.2 GB at Q5 quantization including runtime overhead, so any GPU with 6 GB runs it with headroom.
Can Whisper large-v3 run without a GPU?
Yes. whisper.cpp runs Whisper large-v3 on CPU at roughly real-time speed on modern 8-core processors, and the large-v3-turbo variant is about 8× faster with slightly lower accuracy, per OpenAI’s model release.
Related Pages
Full Whisper large-v3 fit page · All AI models · GeForce RTX 5090 specs · VRAM calculator
VRAM figures are calculated from model architecture parameters using established formulas. Benchmark data is measured and cited per row. GPU memory is vendor_spec from manufacturer datasheets.