LocalClaw/LLM/Ornith 1.0 9B GGUF
Open-weight local LLM

Ornith 1.0 9B GGUF

Compact Ornith 1.0 GGUF variant from DeepReinforce for agentic coding experiments on consumer hardware. MIT licensed and much more practical than the frontier 397B release.

Laptop ready 8 GB RAM Q4_K_M Testing Ornith locally on small machines
Run with LocalClaw Compare all models
Parameters
9B
Minimum RAM
8 GB
Model size
5.8 GB
Quantization
Q4_K_M

Can Ornith 1.0 9B GGUF run locally?

Ornith 1.0 9B GGUF is a good fit for normal laptops and compact desktops with 8 GB RAM or more.

Search for Ornith-1.0-9B-GGUF in LM Studio or another GGUF-compatible runtime.

deepreinforce-ai/Ornith-1.0-9B-GGUF
chatcodereasoningspeedagentictool-callinggeneral

Install path

01
Check RAM fitMinimum 8 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch Ornith-1.0-9B-GGUF in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Practical GGUF release for consumer hardware
  • Much easier to test locally than the 35B and 397B variants
  • Agentic coding and tool-use oriented model family
  • MIT licensed release
  • Good candidate for 8GB and 16GB LocalClaw recommendations

Limitations

  • Lower ceiling than the 35B and 397B Ornith variants
  • Benchmark data is still early and should be treated cautiously
  • Quality will depend heavily on quantization and runtime settings
  • Not a replacement for larger reasoning or coding models on 32GB+ machines

Best use cases

  • Testing Ornith locally on small machines
  • Fast agentic coding experiments
  • Lightweight local chat and tool-use workflows
  • Comparing compact coding models
  • Entry-level LocalClaw/OpenClaw setups

Capability profile

speed
8
quality
7
coding
8
reasoning
7

Technical notes

Developer
DeepReinforce
License
MIT
Context window
Unknown tokens
Architecture
Compact Ornith 1.0 GGUF release for local agentic coding experiments. It belongs to the same DeepReinforce Ornith family as the 35B and 397B releases, but is sized for normal local inference.

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.

Entry laptop fitMacBook Air 8GBMore headroomMac mini M4 16GBAll compatible picks8GB RAM guide

Similar models to compare

Qwen 3 (8B) 8BDANTE-Mosaic-3.5B 3.08BOrnith 1.0 35B GGUF 35B MoE

Where to go next