text model · DeepSeek-V4 · Windows
Can I run DeepSeek-V4-Flash on Nvidia GeForce RTX 4090 (24GB)?
No. DeepSeek-V4-Flash needs ~179.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4090 (24GB) only has ~23 GB usable.
Needs ~179.7 GB even at Q4_K_M, but only ~23 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 156.7 GB: DeepSeek-V4-Flash needs roughly 179.7 GB at Q4_K_M and Nvidia GeForce RTX 4090 (24GB) leaves only about 23 GB usable for a model. The lightest tracked hardware that runs DeepSeek-V4-Flash is the Apple M3 Ultra (256GB) at 256 GB. See DeepSeek-V4-Flash on Apple M3 Ultra (256GB).
- Q4_K_M needed
- ~179.7 GB
- Usable on device
- ~23 GB
- Device memory
- 24 GB
Which quant fits
How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).
- Parameters
- 284B (MoE, 13B active)
- Q4_K_M size
- 174.87 GB
- Q8_0 size
- 302.27 GB
- Context
- 1000k
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Power draw
- ~450 W
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
What you can run instead
Run DeepSeek-V4-Flash on other hardware
FAQ
Can Nvidia GeForce RTX 4090 (24GB) run DeepSeek-V4-Flash?
No. DeepSeek-V4-Flash needs ~179.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4090 (24GB) only has ~23 GB usable.
How much memory does DeepSeek-V4-Flash need?
Nvidia GeForce RTX 4090 (24GB) does not have enough memory. At Q4_K_M the weights are ~174.87 GB; with KV cache and runtime overhead, budget ~179.7 GB at a 4k context. It is a Mixture-of-Experts model (284B total / 13B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run DeepSeek-V4-Flash on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/deepseek-v4-flash/nvidia-rtx-4090-24gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.