16GB Encoder9.51 GB8GB+ VRAMgguf🔒 Gated — HF login required

gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf

Gemma 4 12B with Projection GGUF Q5_K_M (Community)

Community Q5_K_M GGUF quantization of the Gemma 4 text encoder — at 9.51GB, roughly the same footprint as LTX 2.3's Gemma 3 FP4 encoder (9.5GB), which is what makes a 16GB LTX 2.5 setup possible at all. This is the only encoder that fits alongside a GGUF transformer on 16GB. The repo inherits LTX 2.5's gating — sign in and accept the license. Requires the ComfyUI-GGUF custom node to load. Place in models/text_encoders/.

Download gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf

Official HuggingFace repo — sign in and click "Agree and Access" to accept the LTX 2.5 license before this downloads. 9.51 GB · Free.

Install path: ComfyUI/models/text_encoders/ + gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf

No 8GB GPU? Try gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf online — free generation included

Skip the 9.51 GB download and ComfyUI setup. Generate a 6-second video using this exact model in your browser, ~30 seconds.

Try this model online — free →

When to choose gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf

Required if you're building a 16GB LTX 2.5 setup — the official Gemma 4 encoders (15.37GB+) don't leave room for a transformer at that budget.

Will this run on my GPU?

Minimum: 8GB VRAM.

GPUVRAMVerdict
RTX 3060 12GB12GBComfortable
RTX 4060 Ti / 4070 (16GB)16GBComfortable
RTX 4070 Ti SUPER / 4080 (16GB)16GBComfortable
RTX 3090 (24GB)24GBComfortable
RTX 4090 (24GB)24GBComfortable
RTX 5090 / A6000 (32GB+)32GBComfortable

How to use gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf

  1. Download the file from HuggingFace.
  2. Place it in ComfyUI/models/text_encoders/ inside your ComfyUI directory.
  3. Restart ComfyUI (or refresh the model list from the menu).
  4. Load a compatible workflow — see below.

See the LTX 2.5 ComfyUI setup guide for the full file list and install order.

Don't want to run this locally? Try gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf online with a free generation — no GPU, no install, ~30 seconds per clip.

Common issues

ComfyUI doesn't see the file after I downloaded it

Make sure the file is in ComfyUI/models/text_encoders/ (not a subfolder). Restart ComfyUI fully — the menu refresh sometimes misses new files. Filename must match exactly: gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf.

CUDA out of memory error when loading the model

gemma4-12b-with-proj-ltx-2.5-Q5_K_M.gguf needs ~8GB VRAM minimum. If you're hitting OOM: • Enable Sequential Offloading in ComfyUI settings • Lower the resolution (768×512 instead of 1280×704) — both dimensions must be divisible by 32 • Reduce frame count (65 frames instead of 161) — must be 8n+1 • Use a smaller variant — see Related models below.

Free newsletter

Get notified when Gemma 4 12B with Projection GGUF Q5_K_M (Community) updates

Occasional updates on what's new in LTX 2.5 — new quants, LoRAs, releases — with our hands-on verdict on whether they're worth re-downloading. No fixed cadence.

No spam. Sent occasionally when there's real news. Unsubscribe in one click.

Related models