Can the GeForce RTX 4090 run Qwen 3 32B?
Qwen 3 32B runs locally on a 24 GB GPU at Q4_K_M, which needs about 22.7 GB of VRAM with a 4k-token context. Qwen 3 32B is a dense 32.8-billion-parameter model with a native 40,960-token context, so longer contexts scale the KV cache to about 30.2 GB at 32k tokens.
At Q4_K_M quantization with 16,384 context, the Qwen 3 32B requires approximately 25.94GB of VRAM. The GeForce RTX 4090 has 24GB available (1.94GB shortfall).
VRAM Breakdown
| Component | Size (GB) | Source |
|---|---|---|
| Model weights (Q4_K_M) | 19.68 | calculated |
| Loading overhead (10%) | 1.97 | calculated |
| KV cache @ 16,384 context | 4.29 | calculated |
| Total required | 25.94 | |
| GPU memory available | 24 | vendor_spec |
| Headroom / shortfall | -1.94 |
Quantization Options
| Quant | Weights (GB) | Total @ 4K (GB) | Total @ 32K (GB) | Fits GeForce RTX 4090? |
|---|---|---|---|---|
| Q4_K_M | 19.68 | 22.72 | 30.24 | Yes |
| Q5_K_M | 23.37 | 26.78 | 34.3 | No |
| Q6_K | 27.06 | 30.84 | 38.36 | No |
| Q8_0 | 34.85 | 39.41 | 46.93 | No |
| FP16 | 65.6 | 73.23 | 80.75 | No |
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If It Doesn't Fit: Alternatives
Multi-GPU Config
Two of these cards together (~90% parallel efficiency) cover the 25.94GB requirement. See our multi-GPU guide for setup.
Same GPU, Other Models
Frequently Asked Questions
Can the Qwen 3 32B run on 24GB VRAM?
Yes. At Q4_K_M quantization with 4K context, the Qwen 3 32B needs approximately 25.94GB. Your 24GB of usable memory has 1.94GB shortfall.
What is the maximum context length I can use on the GeForce RTX 4090?
The Qwen 3 32B supports up to 40,960 tokens of context. Larger context increases KV-cache memory requirements. At 4K context the model needs ~25.94GB; at 32K it needs more.
Which quantization should I use with the GeForce RTX 4090?
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 large is the Qwen 3 32B Q4_K_M file on disk?
The gguf Q4_K_M artifact is 19.76 GB on disk (ai_model_artifacts.size_bytes, bartowski/Qwen_Qwen3-32B-GGUF). That is a download size, not runtime VRAM. Calculated runtime VRAM at Q4_K_M with 4K context is 22.72 GB (ModelFitService weights + 10% overhead + KV cache).
How much calculated VRAM does Qwen 3 32B need on a 24 GB GPU?
Calculated VRAM is 22.72 GB at Q4_K_M with 4K context versus 24 GB vendor_spec VRAM on GeForce RTX 3090 / RTX 4090 (products.specifications.vram_gb). Headroom is 1.28 GB. No tokens-per-second figure is shown: no exact product x model benchmark row.
Related Pages
Full Qwen 3 32B fit page · All AI models · GeForce RTX 4090 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.