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mmproj) so a single ollama pull yields a model that
does both text and image input — no manual assembly.gemma-4-26B-A4B-it-UD-Q5_K_M.gguf — language weights (Unsloth Dynamic UD-Q5_K_M, ~21 GB)mmproj-F16.gguf — gemma4 vision projector (~1.2 GB)1ollama pull hf.co/mgpwnz/gemma4-q5-vision:Q5_K_M
2ollama show hf.co/mgpwnz/gemma4-q5-vision:Q5_K_M # capabilities must include "vision"mmproj-F16.gguf).⚠️ A bare pull uses Ollama's auto-derived chat template, which can leak gemma<|channel>thinking tokens into the output. For a clean/raw-prompt setup, build the tag from the GGUFs with a minimal Modelfile (TEMPLATE {{ .Prompt }}+PARSER gemma4+PARAMETER stop <turn|>) — twoFROMlines: the language gguf +mmproj-F16.gguf. Text output is then identical to the plain UD-Q5_K_M build (same weights; the projector is inert on the text path).