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majentik/gemma-4-12B-RotorQuant-GGUF-Q3_K_M
gemma-4-12B-RotorQuant-GGUF-Q3_K_M is a text generation model from majentik. Use it when you need the model to write or continue text. It is set up for gguf. The card lists the license as gemma.
[!TIP] KV-cache quantization (upstream, no fork needed): llama.cpp/Ollama cover this natively — -ctk q80 -ctv q80 (~half KV memory, negligible quality loss) or -ctk q40 -ctv q40 (~quarter memory, small quality cost).…
Downloads · 30 days
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From the Hugging Face model README
[!TIP] KV-cache quantization (upstream, no fork needed): llama.cpp/Ollama cover this natively —
-ctk q8_0 -ctv q8_0(~half KV memory, negligible quality loss) or-ctk q4_0 -ctv q4_0(~quarter memory, small quality cost). In Ollama:OLLAMA_KV_CACHE_TYPE=q8_0withOLLAMA_FLASH_ATTENTION=1.
google/gemma-4-12B @ 023679ed352de9bb66cc873c9009ce3482585c08 quantized pack, published as majentik/gemma-4-12B-RotorQuant-GGUF-Q3_K_M.
llama.cpp Q3_K_M quantization, text-only (vision/audio not included).
Released under the RotorQuant line. RotorQuant and TurboQuant are this project's release labels for this pack, not distinct quantization algorithms — both brand repos for a given tier carry byte-identical weights, produced once and published under two names. No brand-specific speedup is claimed or measured for either label.
TEXT-ONLY. This is a llama.cpp GGUF conversion of the text tower only — the vision and audio towers are NOT included in this pack. Do not expect image or audio understanding from this repo; use one of the MLX packs for multimodal input.
Governed by the Gemma Terms of Use. See the upstream repo for the full license text.