Home / Models / GPT-OSS 20B / NVIDIA RTX A4000 16 GB
Can GPT-OSS 20B run on NVIDIA RTX A4000 16 GB?
Yes. Calculated memory fit: GPT-OSS 20B can run entirely in this GPU’s usable VRAM at one or more supported quantizations.
Can it run?
- Can it run?
- Yes, full GPU fit (calculated estimate).
- Full GPU fit?
- Yes
- Model
- GPT-OSS 20B · 22B
- GPU
- NVIDIA RTX A4000 16 GB · 16 GB advertised
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 12.6 GB |
|---|---|
| KV cache | 0.4 GB |
| Runtime reserve | 1.1 GB |
| Safety margin | 0.6 GB |
| Required (estimated) | 14.7 GB |
| GPU usable VRAM | 14.4 GB |
Result: CPU RAM OFFLOAD REQUIRED
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|---|---|
| BF16 | No | No | No | No | No | No | No |
| FP16 | No | No | No | No | No | No | No |
| Q3 | Fits | Fits | Fits | Fits | Fits | Limited context | Limited context |
| Q4 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| Q5 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| Q6 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| Q8 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
What fits entirely in VRAM?
- Q3 at 16K context
- Q3 at 2K context
- Q3 at 32K context
- Q3 at 4K context
- Q3 at 8K context
What requires RAM offload?
Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.
Available graphics cards
These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.
Sources
Model: official config openai/gpt-oss-20b (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.