Compatibility Check
Can I Run GPT-OSS 20B on NVIDIA GeForce RTX 2070 Super?
Sort of — NVIDIA GeForce RTX 2070 Super can run GPT-OSS 20B (FP16) only by spilling layers to RAM. Generation will be slow.
Estimated ~4 tokens/sec on the FP16 quantization.
Hybrid CPU+GPU
Best variant: FP16
CPU + GPU hybrid — not enough VRAM (8 GB < 46 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.
- GPU VRAM
- 8 GB
- Min VRAM (best fit)
- 46 GB
- Recommended VRAM
- 52 GB
- Estimated tok/s
- ~4
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Every GPT-OSS 20B quantization on NVIDIA GeForce RTX 2070 Super
Each row runs the compatibility engine against your VRAM, RAM, and the model's requirements.
| Quantization | File Size | Min VRAM | Rec VRAM | Context | Verdict | Estimated tok/s |
|---|---|---|---|---|---|---|
| Q4_K_M | 10 GB | 11.5 GB | 13 GB | 8K / 8K | Hybrid CPU+GPU | ~12 |
| Q5_K_M | 12.5 GB | 14.4 GB | 16.3 GB | 8K / 8K | Hybrid CPU+GPU | ~10 |
| Q8_0 | 20 GB | 23 GB | 26 GB | 8K / 8K | Hybrid CPU+GPU | ~7 |
| FP16Best fit | 40 GB | 46 GB | 52 GB | 8K / 8K | Hybrid CPU+GPU | ~4 |
Upgrade options that fit GPT-OSS 20B better
Rent GPU instead of buying one
If local fit is weak, cloud GPU gets you running today without hardware upgrade.