Qwen3.5 9B Instruct quants compared
25 GGUF builds by real file size, probed from bartowski/Qwen_Qwen3.5-9B-GGUF on Hugging Face (2026-09-02). 9B params.
Download Qwen3.5 9B Instruct Q4_K_M (5.75 GB) — it fits 8 GB of memory with 16k context. With Ollama: ollama run qwen3.5:9b
Every Qwen3.5 9B Instruct quant by real file size
| Quant | Weights | + KV (16k) | Total | Fits comfortably in | Quality |
|---|---|---|---|---|---|
| BF16 | 17.14 GB | 0.5 GB | 17.6 GB | 24 GB | Full precision (lossless) |
| Q8_0 | 9.13 GB | 0.5 GB | 9.6 GB | 12 GB | Near-lossless |
| Q6_K_L | 7.87 GB | 0.5 GB | 8.4 GB | 12 GB | Excellent |
| Q6_K | 7.41 GB | 0.5 GB | 7.9 GB | 12 GB | Excellent |
| Q5_K_L | 7.21 GB | 0.5 GB | 7.7 GB | 12 GB | Very high |
| Q5_K_M | 6.62 GB | 0.5 GB | 7.1 GB | 8 GB | Very high |
| Q5_K_S | 6.32 GB | 0.5 GB | 6.8 GB | 8 GB | Very high |
| Q4_K_M * | 5.75 GB | 0.5 GB | 6.3 GB | 8 GB | High — the default pick |
| Q4_K_L | 6.45 GB | 0.5 GB | 7.0 GB | 8 GB | High |
| Q4_1 | 5.78 GB | 0.5 GB | 6.3 GB | 8 GB | High |
| Q4_K_S | 5.45 GB | 0.5 GB | 6.0 GB | 8 GB | High |
| Q4_0 | 5.35 GB | 0.5 GB | 5.8 GB | 8 GB | High |
| IQ4_NL | 5.34 GB | 0.5 GB | 5.8 GB | 8 GB | High |
| IQ4_XS | 5.12 GB | 0.5 GB | 5.6 GB | 8 GB | High |
| Q3_K_XL | 5.83 GB | 0.5 GB | 6.3 GB | 8 GB | Acceptable — visible loss |
| Q3_K_L | 5 GB | 0.5 GB | 5.5 GB | 8 GB | Acceptable — visible loss |
| Q3_K_M | 4.82 GB | 0.5 GB | 5.3 GB | 8 GB | Acceptable — visible loss |
| IQ3_M | 4.64 GB | 0.5 GB | 5.1 GB | 8 GB | Acceptable — visible loss |
| Q3_K_S | 4.59 GB | 0.5 GB | 5.1 GB | 8 GB | Acceptable — visible loss |
| IQ3_XS | 4.49 GB | 0.5 GB | 5.0 GB | 8 GB | Acceptable — visible loss |
| IQ3_XXS | 4.22 GB | 0.5 GB | 4.7 GB | 8 GB | Acceptable — visible loss |
| Q2_K_L | 4.95 GB | 0.5 GB | 5.5 GB | 8 GB | Experimental — not ranked — never recommended |
| Q2_K | 4.03 GB | 0.5 GB | 4.5 GB | 8 GB | Experimental — not ranked — never recommended |
| IQ2_M | 3.75 GB | 0.5 GB | 4.3 GB | 8 GB | Experimental — not ranked — never recommended |
| IQ2_S | 3.24 GB | 0.5 GB | 3.7 GB | 8 GB | Experimental — not ranked — never recommended |
* default pick. Weights = real GGUF file sizes from bartowski/Qwen_Qwen3.5-9B-GGUF (probed 2026-09-02). KV = fp16 estimate; a q8_0 cache roughly halves it. "Comfortable" = weights + KV within 90% of memory.
Best Qwen3.5 9B Instruct quant by memory
| Memory | Recommended quant | Total (16k ctx) |
|---|---|---|
| 8 GB | Q5_K_M | 7.1 GB |
| 12 GB | Q8_0 | 9.6 GB |
| 24 GB | BF16 | 17.6 GB |
Why we don't rank Qwen3.5 9B Instruct's 2-bit quants
Quants at 2 bits per weight or below (Q2_K, IQ2, IQ1, TQ1) cut file size by roughly half versus Q4, but the quality collapse is steep and non-linear: perplexity spikes, instruction-following degrades, and hallucinations rise. A model that answers faster but wrong is not a smaller model — it is a worse one. ModelFit lists these builds for completeness but never ranks or recommends them.
Frequently asked questions
What is the best quantization of Qwen3.5 9B Instruct?
Q4_K_M is the default pick: 5.75 GB of weights, high — the default pick quality, fitting comfortably in 8 GB of memory (weights + 16k context KV-cache). Go Q6_K or Q8_0 if you have headroom.
How much memory does Qwen3.5 9B Instruct need?
At Q4_K_M, Qwen3.5 9B Instruct needs 5.75 GB for the weights plus ~0.5 GB of KV-cache at 16k context — about 6.3 GB total, so a 8 GB card or Mac (90% usable budget) runs it comfortably.
Should I use a Q2_K or IQ2 quant of Qwen3.5 9B Instruct?
No. Qwen3.5 9B Instruct at 2 bits per weight is a visibly worse model — quality collapse at that bitrate is steep, not gradual. If only a 2-bit build fits your memory, run a smaller model at Q4_K_M instead. ModelFit lists these builds but never recommends them.
Cite this page
ModelFit: Qwen3.5 9B Instruct quantization comparison (real GGUF file sizes). https://modelfit.io/quant-compare/qwen3.5-9b/ (data probed 2026-09-02, CC BY 4.0).