--- title: MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF canonical_url: "https://www.modelscope.cn/models/Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF" md_url: "https://www.modelscope.cn/models/Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF.md" repository: Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF last_updated: 2026-04-16 license: apache-2.0 pipeline_tag: image-text-to-text tasks: - image-text-to-text base_model: - google/gemma-4-26B-A4B-it base_model_relation: finetune library_name: - gguf - pytorch frameworks: - pytorch language: - en downloads: 115 stars: 0 tags: - gemma4 - gemma - google - gguf - moe - mixture-of-experts - zero-refusals - prism-dq - dynamic-quantization - multimodal - vision - video-text-to-text - image-text-to-text - abliterated - text-generation --- # MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF > MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF - Ex0bit 在 ModelScope 开源的模型。MYTHOS-26B-A4B — PRISM Dynamic Quantization (GGUF) Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF 是 ModelScope 魔搭社区上的image-text-to-text模型，采用 apache-2.0 许可，基于 google/gemma-4-26B-A4B-it 构建。 - **Repository**: Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF - **License**: apache-2.0 - **Tasks**: image-text-to-text - **Base model**: google/gemma-4-26B-A4B-it - **Tags**: gemma4, gemma, google, gguf, moe, mixture-of-experts, zero-refusals, prism-dq, dynamic-quantization, multimodal, vision, video-text-to-text, image-text-to-text, abliterated, text-generation - **Downloads**: 115 - **Stars**: 0 - **Last updated**: 2026-04-16 Source: https://www.modelscope.cn/models/Ex0bit/MYTHOS-26B-A4B-PRISM-PRO-DQ-GGUF --- [![Parameters](https://img.shields.io/badge/Parameters-26B_A4B_MoE-blue)]() [![Format](https://img.shields.io/badge/Format-GGUF-red)]() [![Quant](https://img.shields.io/badge/Quant-PRISM_Dynamic_(5.73_BPW)-yellow)]() [![Multimodal](https://img.shields.io/badge/Multimodal-Vision%20%2B%20Video%20%2B%20Text-purple)]()
# MYTHOS-26B-A4B — PRISM Dynamic Quantization (GGUF) **Gemma 4 26B-A4B MoE PRISM-PRO-Dynamic-Quant** - **PRISM-PRO**: Production model with full over-refusal and bias mechanisms completely removed using State of the Art **PRISM pipeline**. - **DQ**: Per-tensor-class mixed-precision allocation derived entirely from weight structure sensitivity analysis — not closed-gated datasets. Created by [Ex0bit](https://hf.co/Ex0bit) ---
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--- ## Model Details | Property | Value | |----------|-------| | Base Model | google/gemma-4-26B-A4B-it | | Architecture | Gemma 4 MoE (128 experts, top-8 routing) | | Parameters | 26B total / 4B active per token | | Quantization | PRISM-PRO-DYNAMIC-QUANT | | Achieved BPW | 5.73 | | File Size | ~17 GB (language) + ~1.2 GB (vision projector) | | Context Length | 262,144 tokens | | Modalities | Text, Image, Video | | Creator | [Ex0bit](https://hf.co/Ex0bit) | ## Supported Modalities - **Text**: Full instruction-following and chat - **Image**: Vision understanding via SigLIP encoder (280 soft tokens per image) - **Video**: Gemma4VideoProcessor (32 frames, pooled) > Note: This 26B MoE variant does not include audio support. For audio, see the 31B dense variant. ## Files | File | Size | Purpose | |------|------|---------| | `mythos-26b-a4b-prism-pro-dq.gguf` | 17 GB | Language model (quantized) | | `mmproj-mythos-26b-a4b-prism-pro.gguf` | 1.2 GB | Vision projector (F16) | Both files are required for multimodal inference. For text-only use, only the language model file is needed. ## PRISM-DQ Quantization This model uses **PRISM-PRO Dynamic Quantization** — a per-tensor-class mixed-precision allocation that assigns different quantization types to different tensor classes based on weight structure sensitivity. Unlike uniform quantization (Q4_K_M, Q5_K_M), PRISM-DQ analyzes each tensor class's sensitivity and allocates precision where it matters most. Attention projections receive higher precision than FFN layers, with block-level overrides that protect critical layers. The result: BF16-equivalent quality at 5.73 bits-per-weight — a 64% size reduction with zero measurable quality loss. ## Usage ### llama.cpp (multimodal with vision) ```bash llama-mtmd-cli \ --model mythos-26b-a4b-prism-pro-dq.gguf \ --mmproj mmproj-mythos-26b-a4b-prism-pro.gguf \ --image path/to/image.jpg \ --prompt "Describe this image." \ -ngl 99 ``` ### llama.cpp (text-only server) ```bash llama-server \ --model mythos-26b-a4b-prism-pro-dq.gguf \ --port 8080 -ngl 99 ``` ### LM Studio Download both `mythos-26b-a4b-prism-pro-dq.gguf` and `mmproj-mythos-26b-a4b-prism-pro.gguf`. LM Studio will automatically detect the vision projector for multimodal chat. ## Refusal & Bias Removal This model has been treated to remove bias, over-refusals and propaganda from the base google/gemma-4-26B-A4B-it using the State of The Art PRISM pipeline. ## License Apache 2.0 (inherited from google/gemma-4-26B-A4B-it) ## Credits - Creator: [Ex0bit](https://hf.co/Ex0bit) - Base model: [Google DeepMind](https://deepmind.google/models/gemma/gemma-4/) - Quantization engine: PRISM-DQ by [Ex0bit](https://hf.co/Ex0bit)