Can the Arc B580 12 GB run LTX-2.5 (22B)?
Nothing fits entirely, but Q2_K (8.8 GB) overflows by only about 1.6 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | LTX-2.5-Distilled-Q2_K.gguf Q2_K · realrebelai/LTX-2.5_GGUFs | models/unet | 8.8 GB | Download → |
| Text encoder | gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors Gemma 4 12B + LTX projection INT8 (convrot) · Lightricks/LTX-2.5 | models/text_encoders | 15.4 GB | Download → |
| VAE | ltx-2.5-video-vae-bf16.safetensors LTX-2.5 video VAE (DiffVAE) BF16 · Lightricks/LTX-2.5 | models/vae | 1.5 GB | Download → |
| Also needed | ltx-2.5-audio-vae-bf16.safetensors LTX-2.5 audio VAE + vocoder BF16 · Lightricks/LTX-2.5 | models/vae | 0.4 GB | Download → |
| Total download · keep about the same free on disk | 26.0 GB | |||
Alternatives: Gemma 4 12B + LTX projection BF16 (26.3 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. Only for some workflows: LTX-2.5 latent spatial upscaler x2 (1.0 GB, official two-stage template); Gemma 4 E2B INT8 (prompt enhancer, optional) (5.2 GB, only if prompt enhancer enabled). Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.
System RAM: 48 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 26.0 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 32.0 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every LTX-2.5 file on 12 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Lightricks | 42.0 GB | 46.8 GB | 34.8 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · realrebelai | 23.6 GB | 28.4 GB | 16.4 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · realrebelai | 18.7 GB | 23.5 GB | 11.5 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · realrebelai | 16.8 GB | 21.6 GB | 9.6 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · realrebelai | 15.1 GB | 19.9 GB | 7.9 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · realrebelai | 11.5 GB | 16.3 GB | 4.3 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · realrebelai | 8.8 GB | 13.6 GB | spills 1.6 GB | heavy loss; a last resort | Hugging Face → |
Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 4 GB working memory for this model + 0.8 GB kept free for the system.
03The text encoder
Gemma 4 12B (custom LTX-2.5 build): 26.3 GB as 16-bit, 15.4 GB as INT8. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 12 GB the encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.
04About this GPU
Intel Arc GPUs run ComfyUI through PyTorch's native XPU support on Windows 11 and Linux. Memory works the same as on NVIDIA, so the fit verdicts apply. FP8 files save memory but give no speed-up, and some custom nodes are NVIDIA-only.
Arc B580 12 GB: 12 GB GDDR6 · 192-bit · 456 GB/s · Battlemage. Everything that runs on the Arc B580 12 GB →
05What more VRAM would change
With 32 GB you could run LTX-2.5 at 8-bit or better (Q8_0, 23.6 GB) with no offloading: for example on the RTX 5090 32 GB.
What changes from the Arc B580 12 GB to the RTX 5060 Ti 16 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run LTX-2.5 on a Arc B580 12 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does LTX-2.5 need?
Around 13.6 GB with the smallest file (Q2_K) and 28.4 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 46.8 GB.
Which LTX-2.5 file should I download for the Arc B580 12 GB?
Q2_K (8.8 GB) from realrebelai/LTX-2.5_GGUFs. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
Is FP8 faster than GGUF on the Arc B580 12 GB?
No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.
How much do I need to download for LTX-2.5 on the Arc B580 12 GB?
About 26.0 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 12 GB card, 48 GB of system RAM or more is recommended.