Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Yes, comfortably — you'll have ~11.2 GB of headroom running Yi 1.5 34B Chat at Q4_K_M (20.769 GB, ~3 tok/s (est.)) with room for up to 16K context.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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| VRAM | 32 GB unified memory |
| Memory Bandwidth | 120 GB/s |
| Quant | VRAM needed | Fits 32 GB? | Max context |
|---|---|---|---|
| F16 | 70.6 GB | ✗ No | — |
| Q8_0 | 38.4 GB | ✗ No | — |
| Q6_K | 30 GB | ✓ Yes | 8K |
| Q5_K_M | 26.2 GB | ✓ Yes | 16K |
| Q4_K_M | 22.6 GB | ✓ Yes | 16K |
| Q3_K_M | 16.5 GB | ✓ Yes | 16K |
| Q2_K | 13.1 GB | ✓ Yes | 16K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 32 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Yi 1.5 34B Chat | Q4_K_M · 20.769 GB · ~3 tok/s (est.) |
| Yi 1.5 9B Chat | Q4_K_M · 5.3311125 GB · ~11 tok/s (est.) |
At 2 hrs/day, buying (~$999) beats renting at $0.34/hr after about 4.1 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
Yes, comfortably — you'll have ~11.2 GB of headroom running Yi 1.5 34B Chat at Q4_K_M (20.769 GB, ~3 tok/s (est.)) with room for up to 16K context.
Yi 1.5 34B Chat at Q4_K_M quantization (20.769 GB), estimated ~3 tokens/sec, up to 16K context.
| Size | VRAM | Verdict | Speed |
|---|---|---|---|
| Yi 1.5 34B Chat | 20.8 GB | Runs | ~3 tok/s |
| Yi 1.5 9B Chat | 5.3 GB | Runs | ~11 tok/s |
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