Smallest Encoder5.96 GB6GB+ VRAMgguf🔒 Gated — HF login required

gemma4-12b-with-proj-ltx-2.5-Q2_K.gguf

Gemma 4 12B with Projection GGUF Q2_K (Community)

Community Q2_K GGUF quantization of the Gemma 4 text encoder — 5.96GB, the smallest Gemma 4 encoder available for LTX 2.5. Q2_K is an aggressive 2-bit quant; expect weaker prompt adherence than Q4_K_M/Q5_K_M. Use it only when the encoder must be as small as possible and Q4_K_M still doesn't fit your budget. Projection layer bundled. The repo inherits LTX 2.5's gating. Requires the ComfyUI-GGUF custom node. Place in models/text_encoders/.

Released 2026-09-06 · Source: elix3r/gemma4-12b-with-proj-ltx-2.5-GGUF (HuggingFace)Added alongside Q4_K_M in the September update to the repo.

Download gemma4-12b-with-proj-ltx-2.5-Q2_K.gguf

Official HuggingFace repo — sign in and click "Agree and Access" to accept the LTX 2.5 license before this downloads. 5.96 GB · Free.

Install path: ComfyUI/models/text_encoders/ + gemma4-12b-with-proj-ltx-2.5-Q2_K.gguf

No 6GB GPU? Try gemma4-12b-with-proj-ltx-2.5-Q2_K.gguf online — free generation included

Skip the 5.96 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-Q2_K.gguf

Last resort for VRAM — only when Q4_K_M (8.41GB) still doesn't fit your budget. Prompt understanding degrades noticeably at 2-bit, so on 16GB prefer Q4_K_M encoder + Q3_K_S/Q4_K_S transformer over Q2_K encoder + a larger transformer.

Will this run on my GPU?

Minimum: 6GB 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-Q2_K.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-Q2_K.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-Q2_K.gguf.

CUDA out of memory error when loading the model

gemma4-12b-with-proj-ltx-2.5-Q2_K.gguf needs ~6GB 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.

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