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llama.cpp-compatible quantizations of Qwen/Qwen3.5-9B; the underlying weights are unchanged Qwen3.5-9B weights at reduced precision.Text only.Qwen/Qwen3.5-9Bis a multimodal model; these GGUFs contain only the language model (text input -> text output). The vision/video input encoders are not included.
Qwen/Qwen3.5-9B (Apache-2.0, Alibaba Cloud) - these are GGUF quantizations of itOQ-Q4_K_M (higher quality), OQ-Q3_K_M (smaller/faster), and OQ-IQ2_XXS (smallest, mixed i-/k-quant).LICENSE (Custom Model License Agreement).| File | What it is | Size |
|---|---|---|
Qwen3.5-9B-OQ-Q4_K_M.gguf | Language model, OraQuant Q4_K_M (higher quality) | ~5.7 GB |
Qwen3.5-9B-OQ-Q3_K_M.gguf | Language model, OraQuant Q3_K_M (smaller/faster) | ~4.7 GB |
Qwen3.5-9B-OQ-IQ2_XXS.gguf | Language model, OraQuant IQ2_XXS-class (smallest, mixed i-/k-quant) | ~3.2 GB |
LICENSE | Custom Model License Agreement | - |
llama.cpp (no patch required); use a build with Qwen3.5 support.export MODEL=/path/to/Qwen3.5-9B-OQ-Q4_K_M.gguf # or the Q3_K_M / IQ2_XXS file./build/bin/llama-cli -m "$MODEL" -ngl 99-st runs one turn then exits):./build/bin/llama-cli -m "$MODEL" -ngl 99 -st -p "Explain the Chudnovsky algorithm in two sentences."1./build/bin/llama-server -m "$MODEL" -ngl 99 \
2 --alias qwen3.5-9b --host 0.0.0.0 --port 8080--temp 0.6 --top-p 0.95 --top-k 20 --presence-penalty 1.0. Long thinking phases are
normal on hard prompts, especially for the smallest (OQ-IQ2_XXS) footprint.OQ-IQ2_XXS file additionally uses i-quants).Qwen/Qwen3.5-9B weights; no additional training was performed.OQ-Q4_K_M for higher quality, OQ-Q3_K_M for a smaller/faster footprint, OQ-IQ2_XXS for the smallest footprint (expect visible quality loss on the hardest long-reasoning tasks at this size)."Copyright 2025 Alibaba Cloud. Licensed under the Apache License, Version 2.0."