LocalClaw/LLM/Qwen3.8 Flash Next
Open-weight local LLM

Qwen3.8 Flash Next

Catalogue summary: Official Qwen sparse multimodal MoE preview with 125B model parameters plus 51B n-gram embeddings, about 6B active parameters, Qwen Community 1.0 licensing, 262K native context and local Q4_K_M GGUF paths for llama.cpp, Ollama and LM Studio-class runtimes.

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

96 GB catalogue minimum96 GB RAMQ4_K_MCoding assistant
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OllamaNot available for this model
Open on Hugging FaceFiles, licence and available downloadsOpen llama.cpp setupAdvanced option: opens the model filesUse with LocalClawOptional workspace after the model is installed

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Parameters
125B + 51B n-gram (6B active)
Minimum RAM
96 GB
Model size
54.5 GB
Quantization
Q4_K_M

Can Qwen3.8 Flash Next run locally?

Qwen3.8 Flash Next has a catalogue minimum of 96 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use qwen3.8-flash-next as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

Model sourcePublic GGUF repository (verified 2026-09-23): AtomicChat/Qwen3.8-Flash-Next-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningvisionagenticbeastlong-contextmoe

Install path

01
Check RAM fitMinimum 96 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch qwen3.8-flash-next in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: qwen
  • Parameters: 125B + 51B n-gram (6B active)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 96 GB
  • Catalogue model size: 54.5 GB
  • Tags: chat, code, reasoning, vision, agentic, beast, long-context, moe

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
  • beast

Capability profile

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

speed
6
quality
9
coding
10
reasoning
9

Technical notes

Developer
Alibaba Cloud (Qwen Team)
License
Qwen Community License 1.0
Context window
262,144 tokens
Architecture
Sparse multimodal Qwen3.8 Mixture-of-Experts preview with 125B model parameters, about 6B active parameters per token, an additional 51B n-gram embedding table, native 262K context and supported long-context extension toward 1M-token workflows.

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.

Qwen 3.6 35B-A3B 35B (3B active, MoE)Qwen3.8-27B 27BQwen 3.5 MoE (122B/10B active) 122B (10B active)Qwen 3 (32B) 32BQwen 3.5 (27B) 27BQwen 3.6 (27B) 27BQwen AgentWorld 35B-A3B 35B (3B active, MoE)Qwen 2.5 (72B) 72B

Where to go next