OpenAI on NVIDIA Ampere
Can I run gpt-oss 120B-A5.1B on an RTX 3090?
Not at Q4_K_M — it needs 67.4 GB against 21.8 GB available. You would need 4 of these cards.
Won't fit
67.4 GB of 21.8 GB · 310%070 GB
Weights
66.0 GB
KV cache
0.6 GB
Runtime overhead
0.8 GB
Over the limit
45.6 GB
Short by 45.6 GB. You can run it with 11 of 36 layers on the RTX 3090 and the rest in system RAM, at roughly 17.1 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.
Generation17.1tok/s
Prompt processing2924tok/s
Max context0tokens
KV per 1K tokens0GB
Every quantisation of gpt-oss 120B-A5.1B on a RTX 3090
Highlighted row is the highest quality that still fits at 8K context.
| Quantisation | bpw | Weights | Total | Verdict | Max ctx | tok/s |
|---|---|---|---|---|---|---|
| FP16 / BF16 | 16.00 | 217.6 GB | 218.9 GB | Won't fit | — | 4.39 |
| INT8 / W8A8 | 8.50 | 115.3 GB | 116.7 GB | Won't fit | — | 8.76 |
| FP8 (E4M3) | 8.00 | 108.8 GB | 110.1 GB | Won't fit | — | 9.25 |
| Q6_K | 6.56 | 89.2 GB | 90.6 GB | Won't fit | — | 11.8 |
| Q5_K_M | 5.67 | 77.1 GB | 78.5 GB | Won't fit | — | 13.9 |
| Q5_K_S | 5.52 | 75.1 GB | 76.4 GB | Won't fit | — | 14.3 |
| Q4_K_M | 4.85 | 66.0 GB | 67.4 GB | Won't fit | — | 17.1 |
| Q4_K_S | 4.58 | 62.4 GB | 63.8 GB | Won't fit | — | 18.0 |
| Q4_0 | 4.55 | 62.0 GB | 63.4 GB | Won't fit | — | 18.1 |
| AWQ 4-bit | 4.25 | 59.4 GB | 60.7 GB | Won't fit | — | 19.5 |
| GPTQ 4-bit | 4.25 | 59.4 GB | 60.7 GB | Won't fit | — | 19.5 |
| MXFP4 | 4.25 | 59.4 GB | 60.7 GB | Won't fit | — | 19.5 |
| IQ4_XS | 4.25 | 58.0 GB | 59.3 GB | Won't fit | — | 19.9 |
| Q3_K_M | 3.91 | 53.4 GB | 54.7 GB | Won't fit | — | 22.1 |
| IQ3_M | 3.70 | 50.6 GB | 51.9 GB | Won't fit | — | 24.1 |
| IQ3_XXS | 3.06 | 41.9 GB | 43.3 GB | Won't fit | — | 31.8 |
| Q2_K | 2.63 | 36.1 GB | 37.5 GB | Won't fit | — | 41.2 |
| IQ2_XXS | 2.06 | 28.5 GB | 29.8 GB | Won't fit | — | 65.4 |
| IQ1_M | 1.75 | 24.3 GB | 25.7 GB | Won't fit | — | 107 |