Can the RTX 4070 run Qwen2.5-Coder-14B-Instruct?

Just. Qwen2.5-Coder-14B-Instruct at Q4_K_M needs about 10.8 GB of the RTX 4070's 12 GB, running at an estimated 32 tok/s. Keep context short and close other GPU apps.

VRAM
12 GB
Needs at Q4
10.8 GB
Headroom
1.2 GB
Speed (Q4_K_M)
~32 tok/s

Every quantization

Qwen2.5-Coder-14B-Instruct (14.8B) on 12 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M9 GB10.8 GBTight~32 tok/s
Q5_K_M11 GB12.8 GBToo big -
Q8_016 GB17.8 GBToo big -
FP1630 GB31.8 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's 504 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 Qwen/Qwen2.5-Coder-14B-Instruct-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen2.5-Coder-14B-Instruct details →

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Qwen2.5-Coder-14B-Instruct on other hardware

Also runs on the RTX 4070

Frequently asked

Quick answers

Can the NVIDIA RTX 4070 run Qwen2.5-Coder-14B-Instruct?

Just. Qwen2.5-Coder-14B-Instruct at Q4_K_M needs about 10.8 GB of the RTX 4070's 12 GB, running at an estimated 32 tok/s. Keep context short and close other GPU apps.

How much VRAM does Qwen2.5-Coder-14B-Instruct need?

About 9 GB of weights at Q4_K_M, 16 GB at Q8_0 and 30 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen2.5-Coder-14B-Instruct on the RTX 4070?

Roughly 32 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 4070's 504 GB/s memory bandwidth.