LocalClaw/LLM/Ornith-1.5-35B-A3B
Open-weight MoE

Ornith-1.5-35B-A3B

Catalogue summary: Official MIT 35B MoE reasoning model from Ornith AI with about 3B active parameters, 262K context, strong agentic-coding positioning and official Q4_K_M GGUF plus MLX/Ollama/llama.cpp local paths for larger workstations.

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

48 GB catalogue minimum48 GB RAMQ4_K_MCoding assistant
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OllamaNot available for this model
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Parameters
35B (3B active, MoE)
Minimum RAM
48 GB
Model size
21.72 GB
Quantization
Q4_K_M

Can Ornith-1.5-35B-A3B run locally?

Ornith-1.5-35B-A3B has a catalogue minimum of 48 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use ornith-1.5-35b-a3b 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 2026-09-07): ornith-ai/Ornith-1.5-35B-A3B-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningagenticlong-contextpowergeneral

Install path

01
Check RAM fitMinimum 48 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch ornith-1.5-35b-a3b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: ornith
  • Parameters: 35B (3B active, MoE)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 48 GB
  • Catalogue model size: 21.72 GB
  • Tags: chat, code, reasoning, agentic, long-context, power, general

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
  • agentic
  • long-context
  • power

Capability profile

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

speed
5
quality
9
coding
9
reasoning
9

Technical notes

Developer
Ornith AI
License
MIT
Context window
262,144 tokens
Architecture
Sparse 35B mixture-of-experts Ornith-1.5 reasoning model with about 3B active parameters per token, Qwen-style reasoning/tool-call parsing, native 262K context and optional YaRN scaling for longer windows.

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.

Workstation fitMac Studio M4 Max 64GBCUDA workstation classNVIDIA GB10 / DGX SparkLarge local models64GB RAM guide

Related catalogue entries

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

Ornith-1.5-9B 9BNemotron 3.5 Lightning 30B-A3B 30B (3B active, MoE)K2-Horizon-MoVA-36B-A4B 36B (4B active, MoE)Qwen 3.6 35B-A3B 35B (3B active, MoE)Qwen3.8-27B 27BMuse Glimmer 30B 29.8B multimodalKAT-Coder V2.5 Dev 35B (3B active, MoE)Kimi Linear 48B-A3B Instruct 48B (3B active, MoE)

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