LocalClaw/LLM/Ling-2.6-flash (104B MoE)
Public model card reference

Ling-2.6-flash (104B MoE)

Catalogue summary: InclusionAI's MIT-licensed instruct MoE optimized for fast agent workloads. 104B total parameters, only 7.4B active, hybrid linear attention, 262K context and strong tool-use / multi-step execution with high token efficiency.

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

Public model cardNo public GGUF verified104B (7.4B active)2026-04
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Source status
Public model card
Public GGUF
Not verified
Parameters
104B (7.4B active)
Access
Public card

Verified source status

LocalClaw verified a public model card for Ling-2.6-flash (104B MoE) on 2026-09-07, but no public GGUF file in that repository. The catalogue RAM and quantization fields are estimates, not a verified install path.

Only the public model card was verified; no public GGUF file was verified in that repository. Open the model card to confirm current artefacts and supported runtimes. LocalClaw does not claim a one-click LM Studio install.

Public model card (no GGUF file verified 2026-09-07): inclusionAI/Ling-2.6-flashUpstream releasePaper or model cardLicence text
chatcodereasoningspeedquality

Source availability

01
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02
Inspect current filesNo public GGUF file was verified in the repository during the catalogue audit.
03
Confirm a supported runtimeChoose a local runtime only after verifying the exact artefact, licence and hardware requirements upstream.

Catalogue record

  • Family: ling
  • Parameters: 104B (7.4B active)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 80 GB
  • Catalogue model size: 65 GB
  • Tags: chat, code, reasoning, speed, 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
  • speed
  • quality

Capability profile

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

speed
8
quality
9
coding
9
reasoning
8

Technical notes

Developer
InclusionAI / Ant Group
License
MIT
Context window
262,144 tokens
Architecture
Sparse MoE instruct model — 104B total parameters, 7.4B active. Hybrid linear attention using a 1:7 MLA + Lightning Linear architecture, optimized for high-throughput agent inference.

Related catalogue entries

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

Ling-3.0-tiny 7.9B (1.3B active, MoE)Ling Flash Base 2.0 106B (6.1B active, MoE)Qwen 3.5 MoE (122B/10B active) 122B (10B active)Qwen 3 Next (80B/3B MoE) 80B (3B active)Llama-3.3-Nemotron-Super (49B) 49BCommand R+ (104B) 104BDeepSeek V4 Flash Vision Exp 284B (13B active, multimodal MoE)Gemma 4 31B 31B

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