Can I Run DeepSeek V4 Flash on a NVIDIA RTX 4070?
Won't fit — even the smallest quant (Q4_K_M) needs 23.4GB VRAM.
None of DeepSeek V4 Flash's quantizations fit
Even the most aggressive quantization needs more memory than the NVIDIA RTX 4070 provides. Your options below: rent a bigger GPU in the cloud, or upgrade.
Run it in the cloud instead
DeepSeek V4 Flash doesn't fit your 12GB setup. Rent a GPU by the second — no hardware purchase needed.
Per-second GPU rental from $0.20/hr. Spin up an A100, H100, or 4090 in seconds and run any model.
Marketplace of consumer + datacenter GPUs. Often the cheapest spot prices for inference.
On-demand H100s and A100s with reserved-instance pricing for production workloads.
Pay-per-token serverless inference. No GPU setup — just call the API.
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Or upgrade your hardware
GPUs that would let you run this model locally:
Best consumer card for local LLMs — runs most 30B models at Q4-Q5.
Same VRAM as 4090 at half the price on the used market.
All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 12.0GB.
FAQ
Can the NVIDIA RTX 4070 run DeepSeek V4 Flash?
No. DeepSeek V4 Flash (37.0B) needs at least 23.4GB even at its smallest quantization, more than the 12.0GB on the NVIDIA RTX 4070.
What's the best quantization to use?
None of DeepSeek V4 Flash's available quantizations fit in 12.0GB. You'll need either a larger GPU, a smaller model, or to run it in the cloud.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.