LocalClaw/LLM/DeepSeek V4 Flash (284B MoE)
Open-weight local LLM

DeepSeek V4 Flash (284B MoE)

Efficient DeepSeek V4 variant: 284B total, 13B active, 1M-token context. Flash-Max can approach Pro reasoning with larger thinking budget. MIT licensed.

Server-grade 256 GB RAM FP4/FP8 Coding assistant
Run with LocalClaw Compare all models
Parameters
284B (13B active)
Minimum RAM
256 GB
Model size
170 GB
Quantization
FP4/FP8

Can DeepSeek V4 Flash (284B MoE) run locally?

DeepSeek V4 Flash (284B MoE) is server-grade locally. Keep it for comparison unless you have very large unified memory, multiple GPUs or remote inference.

Search for deepseek-v4-flash in LM Studio or another GGUF-compatible runtime.

deepseek-ai/DeepSeek-V4-Flash
chatcodereasoningpoweragenticlong-contextgeneral

Install path

01
Check RAM fitMinimum 256 GB RAM. Start with the FP4/FP8 quant.
02
Load the modelSearch deepseek-v4-flash in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Efficient DeepSeek V4 variant: 284B total, 13B active, 1M-token context. Flash-Max can approach Pro reasoning with larger thinking budget. MIT licensed.

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • code
  • reasoning
  • power
  • agentic
  • long-context

Capability profile

speed
5
quality
9
coding
9
reasoning
9

Technical notes

Developer
deepseek-flash
License
See model repository
Context window
Unknown tokens
Architecture
See model card

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Very large memoryMac Studio Ultra classCheck model size firstNVIDIA GB10 / server optionsMore practical alternativesCompare smaller models

Where to go next