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Run LLM Locally

Qwen3 0.6B on the RTX 5060 Ti 8 GB

With 8 GB of VRAM, the RTX 5060 Ti 8 GB runs Qwen3 0.6B at Q4_K_M entirely on the GPU with an 8K context (about 2.4 GB needed). At Q8_0 it fits entirely.

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Qwen3 0.6B

Q4_K_M · 8K context

Excellent

The model needs about 2.4 GB and fits in the 7.7 GB available, with 5.3 GB to spare.

Your hardware
RTX 5060 Ti 8 GB · 64 GB RAM
Estimated memory
~2.4 GB estimate
VRAM (usable memory)
7.7 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
226–368 tok/s estimate
Largest context in fast memory
32K tokens
Confidence: low

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

Memory breakdown

~2.4 GB (2.1 GB–2.7 GB) needed · estimate

Fits entirely in VRAM · 5.3 GB left

  • Model weights0.5 GB
  • KV cache0.9 GB
  • Runtime overhead0.8 GB
  • Safety margin0.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size

EstimateData updated 24 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 8 GB

Qwen3 0.6B on RTX 5060 Ti 8 GB + 64 GB RAM · 8K context
Qwen3 0.6B Q8_08K~2.5 GB · 205–326 tok/s estimateExcellent
Qwen3 0.6B Q6_K8K~2.5 GB · 207–330 tok/s estimateExcellent
Qwen3 0.6B Q5_K_M8K~2.4 GB · 216–349 tok/s estimateExcellent
Qwen3 0.6B Q4_K_M8K~2.4 GB · 226–368 tok/s estimateExcellent
Qwen3 0.6B IQ4_XS8K~2.3 GB · 231–379 tok/s estimateExcellent
Qwen3 0.6B Q3_K_M8K~2.3 GB · 236–391 tok/s estimateExcellent

Alternatives

GPUs that run Qwen3 0.6B Q4_K_M entirely in VRAM

Other models that fit the RTX 5060 Ti 8 GB

Where to buy a RTX 5060 Ti 8 GB

Prices and links follow the market you choose.

GeForce RTX 5060 Ti 8 GB

8 GB GDDR7 · 448 GB/s · 180 W

ExcellentRuns Qwen3 0.6B Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RTX 5060 Ti 8 GB run Qwen3 0.6B?
The model needs about 2.4 GB and fits in the 7.7 GB available, with 5.3 GB to spare.
Which quantization should I use on the RTX 5060 Ti 8 GB?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~2.5 GB / 7.7 GB.
What is the largest context on the RTX 5060 Ti 8 GB?
At Q4_K_M, about 32K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Qwen3 0.6B (RTX 5060 Ti 8 GB)?
We estimate 226–368 tok/s (estimate, confidence low). Based on: memory bandwidth (448 GB/s) and model size.