Model reference · open weights

Wan2.2-TI2V

Wan2.2-TI2V is an open-weight video model from unsloth, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Video unsloth 1 variants 9k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What Wan2.2-TI2V is

Wan2.2 TI2V 5B, GGUF (mirror) Every GGUF quantisation of Wan2.2-TI2V-5B that QuantStack/Wan2.2-TI2V-5B-GGUF publishes, plus the companion VAE, mirrored here. Unsloth Studio offers this repo as the curated one-click GGUF pick for Wan2.2 TI2V 5B, so its availability is Studio's problem rather than the repacker's: a rename or a takedown turns the pick into a 404 no client can work around. All 13 quants are mirrored, not a chosen few, because the picker lets you choose the precision. The weights are unmodified: byte for byte the files of the same name in the source repo. TI2V-5B is a 720P-only checkpoint: the supported sizes are 1280x704 and 704x1280, and its VAE has temporal compression 4, so valid frame counts are 4k+1. Licence Apache-2.0, from Wan2.2-TI2V-5B. Full text in LICENSE. These files are Derivative Works, not a plain copy: the transformer is quantised and the VAE was converted from the original .pth to .safetensors. Apache-2.0 section 4(b) wants that stated, so NOTICE lists every change along with the attribution. Both sets of changes are QuantStack's work. Not an official Alibaba Wan Team or QuantStack product, and not endorsed by either.

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makerunsloth
TypeVideo models
Variants1
Runs withgguf
Based onWan-AI/Wan2.2-TI2V-5B
Released2026-08-06
Popularity9k downloads / month
Likes8
LicenceOpen weights

How it works

How video models work

Prompt / imagestart pointTemporal diffusionframes over timeVideoMP4 clipA video model generates a sequence of coherent frames from your prompt or a starting image.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
Wan2.2-TI2V-5B-GGUFGGUFWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys unsloth-wan2-2-ti2v for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (unsloth-wan2-2-ti2v below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"unsloth-wan2-2-ti2v","prompt":"a drone shot over a forest"}'

Details

Languages, data & research

Languages

en zh

Tags

gguf ti2v text-to-video en zh

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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