Can the RTX 4070 Ti run Qwen3.5 9B?

Yes. Qwen3.5 9B fits the RTX 4070 Ti's 12 GB at Q4_K_M (about 7.8 GB needed), running at an estimated 67 tok/s. There's room for up to Q8_0 if you want higher quality.

VRAM
12 GB
Needs at Q4
7.8 GB
Headroom
4.2 GB
Speed (Q4_K_M)
~67 tok/s

Every quantization

Qwen3.5 9B (9.7B) on 12 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M6 GB7.8 GBFits~67 tok/s
Q5_K_M7 GB8.8 GBFits~58 tok/s
Q8_010 GB11.8 GBTight~40 tok/s
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 4070 Ti's 504.2 GB/s bandwidth (XiongjieDai/GPU-Benchmarks-on-LLM-Inference). 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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Same model, other hardware - and other models on this card

Qwen3.5 9B on other hardware

Also runs on the RTX 4070 Ti

Frequently asked

Quick answers

Can the GeForce RTX 4070 Ti run Qwen3.5 9B?

Yes. Qwen3.5 9B fits the RTX 4070 Ti's 12 GB at Q4_K_M (about 7.8 GB needed), running at an estimated 67 tok/s. There's room for up to Q8_0 if you want higher quality.

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 4070 Ti?

Roughly 67 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 4070 Ti's 504.2 GB/s memory bandwidth.