Yi 1.5 34B Chat — VRAM, Speed & Local Setup

Written by Jakub Rusinowski · Last updated May 13, 2024

Model library → Yi 1.5 Family → Yi 1.5 34B Chat

A balanced powerhouse. Offers performance close to 70B models but fits on dual 3090s or 24GB cards with tight quantization.

Yi 1.5 34B Chat needs about 22 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters34 Billion
Context window32,000
ArchitectureDense
Provider01.AI
LicenceYi License
Specified atQ4_K_M
System RAM32 GB
Record updated2024-05-13

Licence

Yi License — commercial use permitted. Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K11.3 GB14.1 GB~54 tok/s (est.)Fits comfortably
Q3_K_M14.7 GB17.5 GB~44 tok/s (est.)Fits comfortably
Q4_K_M20.8 GB23.6 GB~32 tok/s (est.)Tight fit
Q5_K_M24.4 GB27.2 GB~4 tok/s (est.)Offloads to system RAM (slow)
Q6_K28.2 GB31.0 GB~4 tok/s (est.)Offloads to system RAM (slow)
Q8_036.5 GB39.4 GB~3 tok/s (est.)Offloads to system RAM (slow)
F1668.8 GB71.6 GB—Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the Yi 1.5 34B Chat VRAM calculator.

Buy This HardwareAMD Radeon RX 7900 XTX 24GB — 24 GB VRAM · 355 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Yi 1.5 34B Chat is the AMD Radeon RX 7900 XTX (24 GB).

Affiliate disclosure: Some links on this page are affiliate links — if you buy through them, LLM Configurator may earn a commission at no extra cost to you. As an Amazon Associate, LLM Configurator earns from qualifying purchases.
AMD Radeon RX 7900 XTX 24GB
24 GB VRAM · 355 W board power
2026 prices are volatile — check the current listing.
Check price on Amazon

How to Run Yi 1.5 34B Chat

Install Ollama, then run:

ollama run yi:34b

Weights on Hugging Face: 01-ai/Yi-1.5-34B-Chat.

Best for: chat, coding, multilingual.

Can I Run Yi 1.5 34B Chat on My GPU?

Other Yi 1.5 Family Sizes

Yi 1.5 34B Chat — Frequently Asked Questions

How much VRAM does Yi 1.5 34B Chat need?
About 22 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Yi 1.5 34B Chat run on an RTX 4090 (24 GB)?
Yes. Yi 1.5 34B Chat needs about 22 GB at Q4_K_M, inside a 24 GB card, at an estimated 32 tokens/sec.
How do I run Yi 1.5 34B Chat locally?
Install Ollama and run `ollama run yi:34b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Yi 1.5 Family come in?
Yi 1.5 34B Chat (22 GB), Yi 1.5 9B Chat (6 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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