Can the RTX 3070 Ti Mobile run Qwen3-4B-Instruct-2507?

Yes. Qwen3-4B-Instruct-2507 fits the RTX 3070 Ti Mobile's 8 GB at Q4_K_M (about 3.8 GB needed), running at an estimated 128 tok/s. There's room for up to Q8_0 if you want higher quality.

VRAM
8 GB
Needs at Q4
3.8 GB
Headroom
4.2 GB
Speed (Q4_K_M)
~128 tok/s

Every quantization

Qwen3-4B-Instruct-2507 (4B) on 8 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M2 GB3.8 GBFits easily~128 tok/s
Q5_K_M3 GB4.8 GBFits easily~86 tok/s
Q8_04 GB5.8 GBFits~64 tok/s
FP168 GB9.8 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 3070 Ti Mobile's 448 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/Qwen3-4B-Instruct-2507-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3-4B-Instruct-2507 details →

Compare

Same model, other hardware - and other models on this card

Qwen3-4B-Instruct-2507 on other hardware

Also runs on the RTX 3070 Ti Mobile

Frequently asked

Quick answers

Can the GeForce RTX 3070 Ti Mobile run Qwen3-4B-Instruct-2507?

Yes. Qwen3-4B-Instruct-2507 fits the RTX 3070 Ti Mobile's 8 GB at Q4_K_M (about 3.8 GB needed), running at an estimated 128 tok/s. There's room for up to Q8_0 if you want higher quality.

How much VRAM does Qwen3-4B-Instruct-2507 need?

About 2 GB of weights at Q4_K_M, 4 GB at Q8_0 and 8 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3-4B-Instruct-2507 on the RTX 3070 Ti Mobile?

Roughly 128 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 3070 Ti Mobile's 448 GB/s memory bandwidth.