Skip to content
Run LLM Locally

Qwen3 30B-A3B on the RTX 4080

Qwen3 30B-A3B at Q4_K_M needs about 19.7 GB, more than the 16 GB of the RTX 4080: part of the model runs from system RAM, which slows generation. At Q3_K_M it fits entirely.

Qwen3 30B-A3B

Q4_K_M · 8K context

CPU/GPU offload

The model needs about 19.7 GB but only 15.5 GB of VRAM is usable: 4.2 GB must be loaded into system RAM. It runs, 79% on the GPU, but more slowly.

Your hardware
RTX 4080 16 GB · 64 GB RAM
Estimated memory
~19.7 GB estimate
VRAM (usable memory)
15.5 GB
GPU only
No
CPU/GPU offload
Required (4.2 GB)
Generation speed
27–54 tok/s estimate
Largest context in fast memory
None
Confidence: low

Based on: memory bandwidth (717 GB/s) and model size · system RAM bandwidth (~51 GB/s)

Memory breakdown

~19.7 GB (19.1 GB–20.5 GB) needed · estimate

4.2 GB must be offloaded to system RAM

  • Model weights17.3 GB
  • KV cache0.8 GB
  • Runtime overhead0.8 GB
  • Safety margin0.9 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
  • split CPU/GPU runs vary a lot with the CPU and PCIe link
  • system RAM speed unknown (dual-channel DDR4-3200 assumed)
  • mixture-of-experts: speed depends on expert routing

Other quantizations on the RTX 4080

Qwen3 30B-A3B on RTX 4080 + 64 GB RAM · 8K context
Qwen3 30B-A3B Q8_08K~33.4 GB · 8.5–17 tok/s estimatePossible but slow
Qwen3 30B-A3B Q6_K8K~26.1 GB · 14–26 tok/s estimateCPU/GPU offload
Qwen3 30B-A3B Q5_K_M8K~22.8 GB · 18–36 tok/s estimateCPU/GPU offload
Qwen3 30B-A3B Q4_K_M8K~19.7 GB · 27–54 tok/s estimateCPU/GPU offload
Qwen3 30B-A3B IQ4_XS8K~17.7 GB · 41–83 tok/s estimateCPU/GPU offload
Qwen3 30B-A3B Q3_K_M8K~15.4 GB · 118–195 tok/s estimateCompatible with limits

Alternatives

Hardware that runs Qwen3 30B-A3B Q4_K_M entirely in memory

Prices and links follow the market you choose.

Radeon RX 7900 XTX

AMD

CompatibleRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

AMD Ryzen AI Max+ 395

Unified memory PC

ExcellentRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

GeForce RTX 2080 Ti

Lowest memory tier

CompatibleRuns Qwen3 30B-A3B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the RTX 4080 run Qwen3 30B-A3B?
The model needs about 19.7 GB but only 15.5 GB of VRAM is usable: 4.2 GB must be loaded into system RAM. It runs, 79% on the GPU, but more slowly.
Which quantization should I use on the RTX 4080?
Q3_K_M is the highest-precision quantization that fits entirely in VRAM at 8K context. ~15.4 GB / 15.5 GB.
What is the largest context on the RTX 4080?
At Q4_K_M, the model does not fit entirely in VRAM even at a short context.
How fast is Qwen3 30B-A3B (RTX 4080)?
We estimate 27–54 tok/s (estimate, confidence low). Based on: memory bandwidth (717 GB/s) and model size, system RAM bandwidth (~51 GB/s).