What GPU do I need to run deepseek-ai/DeepSeek-V4-Flash-0731?

What DeepSeek-V4-Flash-0731 is

DeepSeek-V4-Flash-0731 is DeepSeek's official release of DeepSeek-V4-Flash, a 284B-parameter mixture-of-experts reasoning model with 13B active parameters, the smaller sibling of DeepSeek-V4-Pro with a DSpark speculative-decoding module attached. Its own model card states the same 1,048,576-token (1M) context window, hybrid attention architecture, three reasoning-effort levels (low, high, max), and mixed FP4 (MoE experts) + FP8 (other parameters) published precision as V4-Pro.

License note: fully permissive, no gating and no usage restrictions. Facts in this section are sourced from DeepSeek-V4-Flash-0731's Hugging Face model card, not benchmarked by Aquanode.

What it's used for

• Multi-step reasoning and agentic coding
• Long-context analysis (up to 1M tokens)
• Lower-latency deployment than V4-Pro

Benchmarks (published by DeepSeek)

• Terminal Bench 2.1:82.7source
• HLE (with tools):51.5source

Published by DeepSeek, not measured by Aquanode.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

The SGLang DeepSeek-V4 cookbook linked from DeepSeek's model card lists DeepSeek-V4-Flash-0731 as verified on 4×H200; NVIDIA's own H200 spec lists 141GB HBM3e per GPU, so 4×141GB ≈ 564GB total.

How to run DeepSeek-V4-Flash-0731

vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 \
  --trust-remote-code --kv-cache-dtype fp8 --block-size 256 \
  --data-parallel-size 4 --enable-expert-parallel \
  --moe-backend deep_gemm_mega_moe \
  --attention-config '{"use_fp4_indexer_cache": true}' \
  --speculative-config '{"method":"dspark","num_speculative_tokens":7,"draft_sample_method":"greedy"}'

sglang serve \
  --trust-remote-code \
  --model-path deepseek-ai/DeepSeek-V4-Flash-0731 \
  --tp 4 \
  --moe-runner-backend flashinfer_mxfp4 \
  --speculative-algorithm DSPARK \
  --mem-fraction-static 0.90 \
  --chunked-prefill-size 4096

Deploy DeepSeek-V4-Flash-0731 on Aquanode

Aquanode has no one-click deploy template for DeepSeek-V4-Flash-0731; you install the inference engine yourself with the commands below. Aquanode sells GPU pods billed per second, not a hosted inference API.

1. Launch a bare GPU pod sized to the requirement above (6× RTX PRO 6000 or larger).
2. Open a terminal on the pod, or save one of the commands above as a startup script so it runs automatically the first time the pod boots.
3. Run the command and connect to the resulting endpoint.

Launch a GPU pod

More DeepSeek V4 models

• DeepSeek-V4-Pro-0813 (1650.5B, FP4 + FP8 Mixed)

All 2 DeepSeek V4 models: VRAM and GPU requirements