Can I Run GPT-OSS on NVIDIA GeForce RTX 5060 Ti 8GB?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 sierpnia 2026
No — GPT-OSS 20B at MXFP4 needs 12.1 GB at 8K context (11.1 GB weights + 1 GB KV cache/overhead), and the NVIDIA GeForce RTX 5060 Ti 8GB's 8 GB leaves it ~4.1 GB short. The cheapest card that runs it is the NVIDIA GeForce RTX 4090 Laptop GPU (16 GB).
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NVIDIA GeForce RTX 5060 Ti 8GB Specs
| VRAM | 8 GB |
| Memory Bandwidth | 448 GB/s |
GPT-OSS 20B on the NVIDIA GeForce RTX 5060 Ti 8GB: VRAM by quantization
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 42.8 GB | ✗ No | — | — |
| Q8_0 | 23.2 GB | ✗ No | — | — |
| Q6_K | 18.2 GB | ✗ No | — | — |
| Q5_K_M | 15.8 GB | ✗ No | — | — |
| Q4_K_M | 13.6 GB | ✗ No | — | — |
| Q3_K_M | 9.9 GB | ✗ No | — | — |
| Q2_K | 7.9 GB | ✓ Yes | 8K | — |
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 8 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 5060 Ti 8GB: 8K 12.1 GB ✗ · 32K 12.7 GB ✗ · 128K 15.1 GB ✗. Past 8K it no longer fits 8 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.
Why It Does Not Fit
Every GPT-OSS variant requires more VRAM than the NVIDIA GeForce RTX 5060 Ti 8GB provides (8 GB).
Nearest GPU That Fits
NVIDIA GeForce RTX 4090 Laptop GPU (16 GB VRAM).
GPT-OSS needs ~12 GB but this GPU has 8 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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FAQ
Is the NVIDIA GeForce RTX 5060 Ti 8GB enough to run GPT-OSS locally?
No — GPT-OSS 20B at MXFP4 needs 12.1 GB at 8K context (11.1 GB weights + 1 GB KV cache/overhead), and the NVIDIA GeForce RTX 5060 Ti 8GB's 8 GB leaves it ~4.1 GB short. The cheapest card that runs it is the NVIDIA GeForce RTX 4090 Laptop GPU (16 GB).
What's the cheapest GPU that runs GPT-OSS?
The NVIDIA GeForce RTX 4090 Laptop GPU (16 GB VRAM) is the cheapest upgrade that fits it.
Every GPT-OSS size on the NVIDIA GeForce RTX 5060 Ti 8GB
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| GPT-OSS 120B | 71.6 GB | Does not fit | — |
| GPT-OSS 20B | 12.1 GB | Runs at Q2_K | — |
GPT-OSS on Other GPUs
- GPT-OSS on NVIDIA GeForce RTX 5060
- GPT-OSS on NVIDIA GeForce RTX 4060
- GPT-OSS on NVIDIA GeForce RTX 3070 Ti
- GPT-OSS on NVIDIA GeForce RTX 3070
- GPT-OSS on AMD Radeon RX 9060 XT 8GB
Popular Models on the NVIDIA GeForce RTX 5060 Ti 8GB
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VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
← Can I Run It? | GPT-OSS Model Page | NVIDIA GeForce RTX 5060 Ti 8GB GPU Page | VRAM calculator | Check Your Hardware