LocalClaw/LLM/DeepSeek V4 Flash Vision Exp
Open-weight MoE

DeepSeek V4 Flash Vision Exp

Catalogue summary: Official MIT DeepSeek V4 Flash multimodal experiment with image understanding, 1M context and Unsloth Dynamic GGUF artifacts. The lightest practical GGUF is roughly 82-97GB, while higher-quality Q4/Q8 builds are about 155-162GB, so this belongs on large-memory workstations.

Repository editorial metadata; verify comparative claims in the linked upstream material.

128 GB catalogue minimum128 GB RAMUD-Q2_K_XLCoding assistant
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Parameters
284B (13B active, multimodal MoE)
Minimum RAM
128 GB
Model size
97 GB
Quantization
UD-Q2_K_XL

Can DeepSeek V4 Flash Vision Exp run locally?

DeepSeek V4 Flash Vision Exp has a catalogue minimum of 128 GB RAM with UD-Q2_K_XL. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Treat deepseek-v4-flash-vision-exp as a server-grade catalogue target. Use the verified artefact with a compatible multi-GPU or distributed runtime and follow its upstream instructions; this is not a one-click desktop LM Studio recommendation.

Model sourcePublic GGUF repository (verified 2026-09-07): unsloth/DeepSeek-V4-Flash-Vision-Exp-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningvisionagenticlong-contextquality

Deployment path

01
Check RAM fitServer-grade target. Plan for 128 GB class multi-GPU memory.
02
Load the modelUse deepseek-v4-flash-vision-exp only with a compatible server-grade or distributed runtime; confirm the exact artefact and upstream instructions first.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: deepseek-flash
  • Parameters: 284B (13B active, multimodal MoE)
  • Recommended quantization: UD-Q2_K_XL
  • Catalogue minimum RAM: 128 GB
  • Catalogue model size: 97 GB
  • Tags: chat, code, reasoning, vision, agentic, long-context, quality

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Catalogue tags

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

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
5
quality
10
coding
10
reasoning
10

Technical notes

Developer
DeepSeek AI
License
MIT
Context window
1,048,576 tokens
Architecture
DeepSeek V4 Flash multimodal MoE with about 284B total parameters, roughly 13B active parameters, vision encoder and aligner modules, DFlash attention, MoE layers, Hyper-Connections and DSpark speculative decoding support.

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.

Large unified memoryMac Studio M4 Max 128GB128GB AI PC classNVIDIA GB10 / DGX SparkHigh-memory picks128GB RAM guide

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

DeepSeek V4 Flash 0731 (284B MoE) 284B (13B active)DeepSeek V4 Flash (284B MoE) 284B (13B active)GLM-5.3-Flash 320B (18B active, MoE)Muse Glimmer 30B 29.8B multimodalK2-Horizon-MoVA-36B-A4B 36B (4B active, MoE)Mistral Small 4 (119B-A6.5B) 119B (6.5B active, MoE)Ling Flash Base 2.0 106B (6.1B active, MoE)Qwen 3.6 35B-A3B 35B (3B active, MoE)

Where to go next