What hardware do you need to run DeepSeek-V4-Flash?

A single RTX 5090 cannot hold the full DeepSeek-V4-Flash checkpoint in VRAM. A local setup can combine GPU and system memory, but the exact checkpoint, runtime and context determine its requirements. A low active-parameter count measures work per token, not the storage needed for all model weights.

V4-Flash has documented local serving paths

The KTransformers project's V4-Flash guide documents a hybrid CPU/GPU setup for V4-Flash-0731 using SGLang and KT-Kernel: one RTX 5090 32GB, at least 200GB system RAM and about 340GB storage. Its example configures a 16,384-token context. These are that recipe's requirements, not a universal minimum and not a setup we have benchmarked.

There is also a vLLM V4-Flash serving recipe covering supported data-center hardware. Our earlier statement that local software cannot load V4 was too broad. Follow the chosen runtime's exact model revision, dependency and hardware instructions; support in one runtime does not establish support in another.

Memory: budget for the whole setup

• Weights: use the selected artifact's actual file sizes. Quantization formats have scales and other overhead; nominal bit width alone is not an exact download or allocation estimate.
• Runtime and context: reserve room for KV cache, temporary buffers, operating-system memory and other applications. A context limit in a model card does not prove that your configuration can serve it.
• Offloading: a 32GB GPU paired with substantial system RAM is a different configuration from a model fully resident on that GPU. Disk streaming is another case; neither its latency nor its quality is measured here.

A 512GB Mac Studio has a large unified-memory pool, but memory capacity alone does not verify a compatible Apple runtime, usable context or speed. Read our 512GB Mac Studio guide for the distinction between capacity estimates and measured configurations.

V4.1-Flash is a different checkpoint

The official V4.1-Flash release checked September 10, 2026 describes a 552B backbone with 8B active parameters during prefill and 16B during decode. Those smaller active counts do not make it a 16B-sized download.

Its published tensor index reports 510,286,023,000 bytes: about 510GB, or 475GiB, before runtime overhead. The release already uses mixed low-precision storage. It cannot be fully resident on a 32GB RTX 5090. This is checkpoint analysis, not a V4.1 speed test, and the V4-0731 serving recipe above does not establish V4.1 compatibility.

Measured alternatives and limitations

For configurations we have actually tested on one RTX 5090, see the Gemma 4 12B and Qwen3.8-27B comparison. It reports measured latency, quantization and memory allocation; it does not claim equivalent answer quality to DeepSeek V4 or V4.1. Historical DeepSeek submissions remain available on the cheatsheet.

Reviewed September 10, 2026. No llm-speed V4 or V4.1 benchmark is claimed in this guide. Source specifications, runtime-author configurations and our measured alternatives are separate evidence. See the methodology.