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Run LLM Locally

Qwen3.5 9B on the RTX 5060 Ti 16 GB

With 16 GB of VRAM, the RTX 5060 Ti 16 GB runs Qwen3.5 9B at Q4_K_M entirely on the GPU with an 8K context (about 6.9 GB needed). At Q8_0 it fits entirely.

Qwen3.5 9B

Q4_K_M · 8K context

Excellent

The model needs about 6.9 GB and fits in the 15.5 GB available, with 8.6 GB to spare.

Your hardware
RTX 5060 Ti 16 GB · 64 GB RAM
Estimated memory
~6.9 GB estimate
VRAM (usable memory)
15.5 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
53–72 tok/s estimate
Largest context in fast memory
256K tokens
Confidence: low

Based on: memory bandwidth (448 GB/s) and model size

Memory breakdown

~6.9 GB (6.4 GB–7.4 GB) needed · estimate

Fits entirely in VRAM · 8.6 GB left

  • Model weights5.3 GB
  • KV cache0.3 GB
  • Runtime overhead1 GB
  • Safety margin0.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size

EstimateData updated 40 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet

Other quantizations on the RTX 5060 Ti 16 GB

Qwen3.5 9B on RTX 5060 Ti 16 GB + 64 GB RAM · 8K context
Qwen3.5 9B Q8_08K~10.7 GB · 33–44 tok/s estimateExcellent
Qwen3.5 9B Q6_K8K~8.6 GB · 42–56 tok/s estimateExcellent
Qwen3.5 9B Q5_K_M8K~7.8 GB · 47–63 tok/s estimateExcellent
Qwen3.5 9B Q4_K_M8K~6.9 GB · 53–72 tok/s estimateExcellent
Qwen3.5 9B IQ4_XS8K~6.4 GB · 58–79 tok/s estimateExcellent
Qwen3.5 9B Q3_K_M8K~5.9 GB · 63–86 tok/s estimateExcellent

Alternatives

Where to buy a RTX 5060 Ti 16 GB

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GeForce RTX 5060 Ti 16 GB

16 GB GDDR7 · 448 GB/s · 180 W

ExcellentRuns Qwen3.5 9B Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RTX 5060 Ti 16 GB run Qwen3.5 9B?
The model needs about 6.9 GB and fits in the 15.5 GB available, with 8.6 GB to spare.
Which quantization should I use on the RTX 5060 Ti 16 GB?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~10.7 GB / 15.5 GB.
What is the largest context on the RTX 5060 Ti 16 GB?
At Q4_K_M, about 256K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Qwen3.5 9B (RTX 5060 Ti 16 GB)?
We estimate 53–72 tok/s (estimate, confidence low). Based on: memory bandwidth (448 GB/s) and model size.