Can the RTX 3050 OEM run Qwen3.5 9B?

Just. Qwen3.5 9B at Q4_K_M needs about 7.8 GB of the RTX 3050 OEM's 8 GB, running at an estimated 21 tok/s. Keep context short and close other GPU apps.

VRAM
8 GB
Needs at Q4
7.8 GB
Headroom
0.2 GB
Speed (Q4_K_M)
~21 tok/s

Every quantization

Qwen3.5 9B (9.7B) on 8 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M6 GB7.8 GBTight~21 tok/s
Q5_K_M7 GB8.8 GBToo big -
Q8_010 GB11.8 GBToo big -
FP1619 GB20.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 3050 OEM's 224 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf unsloth/Qwen3.5-9B-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3.5 9B details →

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Qwen3.5 9B on other hardware

Also runs on the RTX 3050 OEM

Frequently asked

Quick answers

Can the GeForce RTX 3050 OEM run Qwen3.5 9B?

Just. Qwen3.5 9B at Q4_K_M needs about 7.8 GB of the RTX 3050 OEM's 8 GB, running at an estimated 21 tok/s. Keep context short and close other GPU apps.

How much VRAM does Qwen3.5 9B need?

About 6 GB of weights at Q4_K_M, 10 GB at Q8_0 and 19 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3.5 9B on the RTX 3050 OEM?

Roughly 21 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 3050 OEM's 224 GB/s memory bandwidth.