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Ex0bit/Qwen3.5-122B-A10B-PRISM-PRO-GGUF
Qwen3.5-122B-A10B-PRISM-PRO-GGUF is a image-text-to-text model from Ex0bit. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as apache-2.0.
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.gguf62.9 GB · 99%
From the Hugging Face model README
PRISM-LITE Version | PRISM VIP Memberships | Ko-fi | Direct Model Purchase
</div>GGUF quantized versions of Qwen3.5-122B-A10B-PRISM-PRO -- an unrestricted PRISM Production model with full over-refusal and bias mechanisms completely removed using our State of the Art PRISM pipeline (Projected Refusal Isolation via Subspace Modification).
If you find PRISM models useful, please consider supporting development:
</div>| Quantization | Size | BPW | Description |
|---|---|---|---|
| Dynamic | 57.7 GB | 4.06 | PRISM Dynamic -- forensic per-block quantization with 5-tier ffn_down_exps allocation |
This is not a standard uniform quantization. PRISM Dynamic uses forensic per-block analysis derived from comprehensive KLD sensitivity scoring to assign optimal quantization types to each tensor block individually:
All attention tensors are preserved at Q8_0. All norms and routing weights are kept at F32. The imatrix used for information-sensitive quantization types is included.
Dynamic/
Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf -- Dynamic quant (57.7 GB)
mmproj-Qwen3.5-122B-A10B-PRISM-PRO.gguf -- Vision encoder (871 MB)
imatrix.dat -- Importance matrix (342 MB)
mmproj GGUF for seamless image and video understanding.# Text-only inference
./llama-cli \
-m Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf \
-p "Hello! Tell me about quantum computing." \
-n 2048 -ngl 999 --temp 0.7
# With vision (multimodal)
./llama-mtmd-cli \
-m Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf \
--mmproj mmproj-Qwen3.5-122B-A10B-PRISM-PRO.gguf \
--image photo.jpg \
-p "Describe this image in detail." \
-n 2048 -ngl 999
# Server mode
./llama-server \
-m Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf \
--mmproj mmproj-Qwen3.5-122B-A10B-PRISM-PRO.gguf \
-ngl 999 --port 8080
koboldcpp \
--model Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf \
--mmproj mmproj-Qwen3.5-122B-A10B-PRISM-PRO.gguf \
--gpulayers 999 \
--contextsize 8192
# Create a Modelfile
cat > Modelfile << 'EOF'
FROM ./Qwen3.5-122B-A10B-PRISM-PRO-Dynamic.gguf
PARAMETER temperature 0.7
PARAMETER top_p 0.95
PARAMETER top_k 20
EOF
ollama create prism-pro -f Modelfile
ollama run prism-pro
| Setup | VRAM Required | Notes |
|---|---|---|
| Dynamic (GPU only) | ~60 GB | Fits on 1x A100 80GB or 1x H100 80GB |
| Dynamic (GPU + CPU offload) | 48+ GB GPU + RAM | Offload some layers to CPU |
| Dynamic (CPU only) | 64+ GB RAM | Slower but functional |
| Benchmark | Qwen3.5-122B-A10B | GPT-5-mini | Qwen3-235B-A22B |
|---|---|---|---|
| MMLU-Pro | 86.7 | 83.7 | 84.4 |
| MMLU-Redux | 94.0 | 93.7 | 93.8 |
| GPQA Diamond | 86.6 | 82.8 | 81.1 |
| HMMT Feb 25 | 91.4 | 89.2 | 85.1 |
| SWE-bench Verified | 72.0 | 72.0 | -- |
| LiveCodeBench v6 | 78.9 | 80.5 | 75.1 |
| MMMU | 83.9 | 79.0 | 80.6 |
| VideoMME (w/ sub) | 87.3 | 83.5 | 83.8 |
Note: Benchmark results are from the base Qwen3.5-122B-A10B model.
Based on Qwen3.5-122B-A10B by the Qwen Team (Alibaba Group). Licensed under Apache 2.0.
Based on Qwen3.5-122B-A10B by the Qwen Team. GGUF conversion and quantization by Ex0bit. See the Qwen3.5 blog post for architecture details.
@misc{qwen35prismpro_gguf,
title = {Qwen3.5-122B-A10B-PRISM-PRO-GGUF},
author = {Ex0bit},
month = {February},
year = {2026}
}