Can I Run GPT-OSS on NVIDIA GeForce RTX 5080?
作者： Jakub Rusinowski · 最后更新： 2026年9月29日
Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), leaving ~3.7 GB of the NVIDIA GeForce RTX 5080's 16 GB, at ~207 tok/s (est.).
See what else this hardware can run →
或在 Vast.ai 比较，低至 $0.35/小时 (typical low · varies)
作为亚马逊联盟成员，我们从符合条件的购买中获得收入。云 GPU 链接为推荐链接——我们可能获得佣金，您无需额外付费。
NVIDIA GeForce RTX 5080 Specs
| VRAM | 16 GB |
| Memory Bandwidth | 960 GB/s |
GPT-OSS 20B on the NVIDIA GeForce RTX 5080: VRAM by quantization
| Quant | VRAM needed | Fits 16 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 43 GB | ✗ No | — | — |
| Q8_0 | 23.4 GB | ✗ No | — | — |
| Q6_K | 18.3 GB | ✗ No | — | — |
| Q5_K_M | 16 GB | ✗ No | — | — |
| Q4_K_M | 13.8 GB | ✓ Yes | 32K | — |
| Q3_K_M | 10.1 GB | ✓ Yes | 64K | — |
| Q2_K | 8.1 GB | ✓ Yes | 128K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At MXFP4 on the NVIDIA GeForce RTX 5080: 8K 12.3 GB · 32K 13.5 GB · 128K 18.3 GB ✗. Past 128K it no longer fits 16 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? GPT-OSS 20B on 16 GB of system RAM, CPU only: runs.
GPT-OSS Sizes That Fit the NVIDIA GeForce RTX 5080 (at 8K context)
| GPT-OSS 20B | MXFP4 · 12.3 GB at 8K context · ~207 tok/s (est.) |
At 2 hrs/day, buying (~$999) beats renting at $0.34/hr after about 4.1 years.
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Is the NVIDIA GeForce RTX 5080 enough to run GPT-OSS locally?
Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), leaving ~3.7 GB of the NVIDIA GeForce RTX 5080's 16 GB, at ~207 tok/s (est.).
What's the best GPT-OSS size for the NVIDIA GeForce RTX 5080?
GPT-OSS 20B at MXFP4 quantization needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), estimated ~207 tokens/sec.
Every GPT-OSS size on the NVIDIA GeForce RTX 5080
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| GPT-OSS 120B | 71.9 GB | Does not fit | — |
| GPT-OSS 20B | 12.3 GB | Runs | ~207 tok/s |
GPT-OSS on Other GPUs
- GPT-OSS on NVIDIA GeForce RTX 5070 Ti
- GPT-OSS on NVIDIA GeForce RTX 5060 Ti 16GB
- GPT-OSS on NVIDIA GeForce RTX 4080 Super
- GPT-OSS on NVIDIA GeForce RTX 4080
- GPT-OSS on NVIDIA GeForce RTX 4070 Ti Super
Popular Models on the NVIDIA GeForce RTX 5080
- DeepSeek R1 on NVIDIA GeForce RTX 5080
- Qwen 3 on NVIDIA GeForce RTX 5080
- Qwen 2.5 Family on NVIDIA GeForce RTX 5080
VRAM Tier
Troubleshooting
Buying Guide
← Can I Run It? | GPT-OSS Model Page | NVIDIA GeForce RTX 5080 GPU Page | VRAM calculator | Check Your Hardware