Can you run Wan 2.2 (A14B & TI2V-5B) locally?

Wan 2.2 family · July 2025 · 27.00B parameters (14B activated per token) · Hugging Face model card

How much VRAM does Wan 2.2 (A14B & TI2V-5B) need at each quantization?

Wan 2.2 (A14B & TI2V-5B) needs 21.8 GB of VRAM at Q4_K_M. The table below lists weights-only size and total VRAM including overhead for each common quantization level including runtime overhead.

Video diffusion transformer — no KV cache. Table adds a 4 GB activation overhead for 720p video latents. The T5-XXL text encoder (~9.4 GB FP16) can be offloaded to CPU; the dense TI2V-5B variant needs only ~5B params.

Method: weights = parameters × bits-per-weight (Q4_K_M ≈ 4.8, Q5_K_M ≈ 5.7, Q6_K ≈ 6.6, Q8_0 ≈ 8.5, FP16 = 16), plus 10% loading overhead, plus KV cache from the verified architecture config (not applicable to this architecture). Source: A14B: 27B total / 14B active per step — HF model card (Wan-AI/Wan2.2-T2V-A14B). TI2V-5B: 5B dense — HF card (Wan-AI/Wan2.2-TI2V-5B).

Which GPUs can run Wan 2.2 (A14B & TI2V-5B) locally?

At Q4_K_M with a 4k context, Wan 2.2 (A14B & TI2V-5B) needs 21.8 GB of VRAM. The lists below are computed live from our GPU database and grouped by how much headroom the card has. Disclosure: CompareAIHardware.com participates in the Amazon Associates program and earns from qualifying purchases through links on this page. Affiliate relationships do not influence our recommendations.

Runs Wan 2.2 (A14B & TI2V-5B) comfortably (25%+ VRAM headroom)

Minimum GPUs that fit Wan 2.2 (A14B & TI2V-5B) at Q4_K_M

These GPUs hold the model but leave little headroom — keep contexts short.

Needs 2+ GPUs to run Wan 2.2 (A14B & TI2V-5B)

One of these cards is too small on its own, but a pair (tensor or pipeline parallel, ~90% efficiency) covers the 21.8 GB requirement. See our multi-GPU guide for setup.

Can a Mac run Wan 2.2 (A14B & TI2V-5B)?

Yes — these Apple Silicon machines fit Wan 2.2 (A14B & TI2V-5B) at Q4_K_M, since macOS lets the GPU use about 75% of unified memory. Generation speed is bound by memory bandwidth, so the GB/s column matters as much as capacity.

Can Wan 2.2 (A14B & TI2V-5B) run on mini PCs, Jetson, or NPU devices?

These edge and NPU devices from our database have enough memory for Wan 2.2 (A14B & TI2V-5B) at Q4_K_M. Their memory bandwidth is far below discrete GPUs, so expect a fraction of desktop generation speed.

Which pre-built systems can run Wan 2.2 (A14B & TI2V-5B)?

These mini PCs and workstations from our database fit Wan 2.2 (A14B & TI2V-5B) at Q4_K_M. Usable-memory figures are conservative: Windows shares about half of system RAM with the GPU by default (Linux can expose more), macOS lets Apple Silicon GPUs use about 75% of unified memory, and Linux unified-memory systems such as GB10 expose roughly 90%. Generation speed is bound by memory bandwidth, so compare the GB/s column before buying.

Frequently asked questions

Related guides

• Best GPU for FLUX.1
• Multi-GPU Guide
• Best GPU for Stable Diffusion