aliteq.

The best GPU for running DeepSeek V4 Pro (MoE) (2026)

Ranked from live rental prices and computed VRAM fit, not opinion. Every card is judged at Q4_K_M — the quantisation most people actually run — at 8k context, so it's a fair comparison. A card that can't fit DeepSeek V4 Pro (MoE)at that quality isn't listed, because it could only run a crushed version.

No single card in our database fits DeepSeek V4 Pro (MoE) at Q4_K_M and 8k context — at 1599B parameters it needs more memory than any one consumer or workstation GPU has, so this is a multi-GPU or datacenter decision.

See one fast card vs two big ones and the cheapest way to serve a 70B, or the full breakdown on the cost-to-run page.

Check it yourself

See exactly what fits, at any context length

Running DeepSeek V4 Pro (MoE): common questions

How much VRAM do you need to run DeepSeek V4 Pro (MoE)?
At Q4_K_M and 8k context, DeepSeek V4 Pro (MoE) needs about 903.5 GB — 902.7 GB of weights plus 0.0 GB of KV cache and ~0.8 GB overhead. So you want a card with at least that much free memory; the KV cache grows if you use longer context.
Can an RTX 4090 run DeepSeek V4 Pro (MoE)?
Not at Q4_K_M — DeepSeek V4 Pro (MoE) needs more than the card's 24 GB at that quality and 8k context. You'd have to drop to a lower quantisation (worse quality), shorten the context, or use a bigger card or two cards.
Can an RTX 3090 run DeepSeek V4 Pro (MoE)?
Not at Q4_K_M — DeepSeek V4 Pro (MoE) needs more than the card's 24 GB at that quality and 8k context. You'd have to drop to a lower quantisation (worse quality), shorten the context, or use a bigger card or two cards.
Can an RTX 4060 Ti 16GB run DeepSeek V4 Pro (MoE)?
Not at Q4_K_M — DeepSeek V4 Pro (MoE) needs more than the card's 16 GB at that quality and 8k context. You'd have to drop to a lower quantisation (worse quality), shorten the context, or use a bigger card or two cards.

Before you buy

GLM-4.5-Air on local hardware

The consumer-runnable GLM: VRAM by quant, which cards and unified-memory boxes clear it, and what to expect from published numbers — the written companion to this page.

Cheapest way to run GLM in the cloud

Air on one 80 GB card, GLM-4.6 on two, GLM-5 on a pair of H200s — the multi-GPU maths with live, dated rental prices.

Run Mistral Small 24B locally

VRAM by quant (Q4 ~14 GB, Q8 ~25 GB, BF16 ~55 GB), which cards clear it, what tokens/s to expect from published benchmarks — and what a 24 GB card rents for when yours doesn't.

Cheapest RTX 4090 rental

Live per-hour 4090 prices on Vast and Runpod, the spot-vs-on-demand lever, and what a 24 GB card actually runs — the rent-a-card answer for everything in the 14B–32B class.

Best GPU for other models

Kimi K3 (MoE)DeepSeek V4.1 Flash (MoE)GLM-5.3 (MoE)MiniMax-M3 (MoE)Qwen3 235B-A22B (MoE)MiniMax-M2.5 (MoE)Qwen3.8-Flash-Next (MoE)Qwen3.5 122B-A10B (MoE)NVIDIA Nemotron 3 Super 120B-A12B (MoE)gpt-oss 120B (MoE)Llama 4 Scout 17B-16E (MoE)GLM-4.5-Air (MoE)