Can I Run Yi 1.5 34B Chat on NVIDIA GeForce RTX 4070 Ti?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 2026

No. Yi 1.5 34B Chat needs 23.6 GB at 8K context (20.8 GB weights + 2.8 GB KV cache/overhead) at Q4_K_M and the NVIDIA GeForce RTX 4070 Ti has only 12 GB. No quantization we publish closes a gap that size.

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The numbers

ModelYi 1.5 34B Chat
Parameters34B
QuantizationQ4_K_M
VRAM needed (8K context)23.6 GB
NVIDIA GeForce RTX 4070 Ti VRAM12 GB
VerdictDoes not fit

Yi 1.5 34B Chat on the NVIDIA GeForce RTX 4070 Ti: VRAM by quantization

QuantVRAM neededFits 12 GB?Max contextWhole PC
F1671.6 GB✗ No——
Q8_039.4 GB✗ No——
Q6_K31 GB✗ No——
Q5_K_M27.2 GB✗ No——
Q4_K_M23.6 GB✗ No——
Q3_K_M17.5 GB✗ No——
Q2_K14.1 GB✗ No——

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 12 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 4070 Ti: 8K 23.6 GB ✗ · 31K 29.4 GB ✗. Past 8K it no longer fits 12 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

What to do next

Either step down to a smaller size in this family, or move to a NVIDIA GeForce RTX 5090 Laptop GPU (24 GB), the card with the least memory we track that holds it.

No compatible GPU? Yi 1.5 34B Chat on 32 GB of system RAM, CPU only: runs comfortably.

Won't fit — rent Yi 1.5 34B Chat instead

Yi 1.5 34B Chat needs ~24 GB but this GPU has 12 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:

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RunPod $0.34/hr
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Other Yi 1.5 Family sizes on the NVIDIA GeForce RTX 4070 Ti

Yi 1.5 34B Chat on nearby hardware

All Yi 1.5 Family sizes on the NVIDIA GeForce RTX 4070 Ti | Yi 1.5 34B Chat model page | NVIDIA GeForce RTX 4070 Ti GPU page | VRAM calculator | Check your hardware