Models › Qwen3.5 9B › RTX 4060 Ti 16GB
Can I run Qwen3.5 9B on RTX 4060 Ti 16GB?
Yes
Yes. Qwen3.5 9B fits fully on the RTX 4060 Ti 16GB at Q8_0 (about 11.6 GB of 16 GB usable, 8k context). ESTIMATE
Verdict by quantization (8k context, f16 KV, 32 GB RAM for offload)
| Quant | Needs | RTX 4060 Ti 16GB (16 GB) |
|---|---|---|
| Q3_K_M | 5.9 GB | ✅ Fits |
| IQ4_XS | 6.3 GB | ✅ Fits |
| Q4_K_M | 7.0 GB | ✅ Fits |
| MXFP4 | 6.7 GB | ✅ Fits |
| Q5_K_M | 8.1 GB | ✅ Fits |
| Q6_K | 9.2 GB | ✅ Fits |
| Q8_0 | 11.6 GB | ✅ Fits |
| F16 | 21.1 GB | 🐢 Needs RAM offload |
Speed
No measured run for this pair yet, and we don't estimate offloaded speeds. Submit a llama-bench run.
Memory figures are estimates from the model's parameter count and config.json (Hugging Face). How we calculate. Last verified with data from 2026-10-20.
FAQ
Can I run Qwen3.5 9B on the RTX 4060 Ti 16GB?
Yes. Qwen3.5 9B fits fully on the RTX 4060 Ti 16GB at Q8_0 (about 11.6 GB of 16 GB usable, 8k context).
How much VRAM does Qwen3.5 9B need?
About 7.0 GB at Q4_K_M and 11.6 GB at Q8_0 with 8k context (estimate).
Qwen3.5 9B on other hardware: RTX 3060 12GB · RTX 5060 Ti 16GB · RTX 3090 · Apple M4 Pro (48 GB)
Other models on RTX 4060 Ti 16GB: gpt-oss 20B (MoE) · Qwen3.6 27B · Qwen3.6 35B A3B (MoE) · Qwen3.8 27B · Gemma 4 26B A4B (MoE) · Gemma 4 12B · Llama 3.1 8B Instruct
See all models for 16 GB VRAM.
Won't fit? Free hosted options: FreeAISwap.