Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
Not at Q4_K_M — that needs 8.5 GB and the NVIDIA GeForce RTX 5060 Ti 8GB has 8 GB. Drop to Q2_K and it fits in 7 GB, with up to 8K of context.
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| Model | Qwen 2.5 14B Instruct |
| Parameters | 14B |
| Quantization | Q4_K_M |
| VRAM needed | 8.5 GB |
| NVIDIA GeForce RTX 5060 Ti 8GB VRAM | 8 GB |
| Verdict | Runs at a lower quant |
| Fits at | Q2_K (7 GB) |
| Max context | 8K |
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 29.6 GB | ✗ No | — | — |
| Q8_0 | 16.5 GB | ✗ No | — | — |
| Q6_K | 13.1 GB | ✗ No | — | — |
| Q5_K_M | 11.5 GB | ✗ No | — | — |
| Q4_K_M | 10.1 GB | ✗ No | — | — |
| Q3_K_M | 7.6 GB | ✓ Yes | 4K | — |
| Q2_K | 6.2 GB | ✓ Yes | 8K | — |
Assumes a 4K-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 Q4_K_M on the NVIDIA GeForce RTX 5060 Ti 8GB: 8K 10.9 GB ✗ · 32K 15.7 GB ✗ · 128K 35 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.
Quantize to Q2_K. That is the cheapest fix — it costs some quality but no money.
No compatible GPU? Qwen 2.5 14B Instruct on 16 GB of system RAM, CPU only: runs, but it is tight.
Running Qwen 2.5 14B Instruct on this card:
Qwen 2.5 14B Instruct needs ~8 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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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
All Qwen 2.5 Family sizes on the NVIDIA GeForce RTX 5060 Ti 8GB | Qwen 2.5 14B Instruct model page | NVIDIA GeForce RTX 5060 Ti 8GB GPU page | Check your hardware