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mu2solutions/Molmo2-O-7B-GGUF
Molmo2-O-7B-GGUF is a image-text-to-text model from mu2solutions. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
GGUF conversion of allenai/Molmo2-O-7B, published by Mu2 Solutions. No GGUF of Molmo2-O-7B was publicly available when this was built (checked 2026-09-28).
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.gguf5.4 GB · 100%
From the Hugging Face model README
GGUF conversion of allenai/Molmo2-O-7B, published by Mu2 Solutions. No GGUF of Molmo2-O-7B was publicly available when this was built (checked 2026-09-28).
Molmo2-O-7B is Allen Institute for AI's fully open multimodal model (Apache 2.0): a SigLIP vision encoder plus a pooling cross-attention projector over a fully open 7B text backbone (olmo2 architecture, per-head QK-norm).
Apache 2.0, same as the source model. No additional restrictions.
| File | Quant | Size | SHA-256 |
|---|---|---|---|
Molmo2-O-7B-text-Q4_K_M.gguf | Q4_K_M (text) | 4.47 GB | 6aaa653f9813c2d0d3bfbd9c1b18ac64f9f82ea25de07286913b65fe43507b4d |
Molmo2-O-7B-mmproj-F16.gguf | F16 (vision projector) | 927 MB | d158daf3c12b0dbb80cb565c83a79ec3601f344789738b3659f53383797d7dc7 |
Load the text quant together with the mmproj to get a working vision model.
Vision requires Mu2's experimental llama.cpp fork. Upstream llama.cpp does not yet support the Molmo2 vision graph, so this mmproj will not load on a stock build. See the 8B repo for the full explanation.
allenai/Molmo2-O-7B, revision 784410650d12 (frozen 2026-01-23)c3d25ece9olmo2clip, 315 tensors (SigLIP ViT, pooling cross-attention, SwiGLU projector), with separate mm.pool.k / mm.pool.v tensors and the baked mm.image_patch_add rowMeasured on Mu2's CPU-only OG Rig (Intel i3-2100, no GPU):
Vision encode: completed in 491,094 ms for one 378x378 view.
Vision generation: asked Describe this image in one sentence. on a real image, the model answered:
The image displays a partially visible logo or advertisement with large, bold text in blue and red colors, featuring fragmented words like "RE-V," "BUSINESS," and "STRA," along
The image is a corporate wordmark on a white background with navy and dark red lettering. The text, the colours and the layout are all correct, so this is a genuine reading of the image rather than a plausible guess.
Command used:
llama-mtmd-cli -m Molmo2-O-7B-text-Q4_K_M.gguf \
--mmproj Molmo2-O-7B-mmproj-F16.gguf \
--image image.jpg -c 4096 -t 4 -n 40 --temp 0 \
-p "Describe this image in one sentence."
<frame_end> tokens after the sentence. Cosmetic; the description itself is intact.</s> token is not control-type and overrides it. The same warning appears on our Molmo2-4B and Molmo2-8B files.llama-mtmd-cli -m Molmo2-O-7B-text-Q4_K_M.gguf \
--mmproj Molmo2-O-7B-mmproj-F16.gguf \
--image photo.jpg -p "Describe this image."