Pluto LM 1.5B
Packaged on HuggingFace & Ollama as Pluto LM
A compact language model fine-tuned for edge inference and IoT agent tasks. Runs on-device. No internet. No data leaves your hardware.
Get the Model
Two ways to run Pluto LM 1.5B locally.
$ ollama pull hf.co/plutoedge/Pluto-LM
Pulls directly from HuggingFace via Ollama. Requires ollama ≥ 0.3.
# Pull base model first
$ ollama pull qwen2.5:1.5b
# Register Pluto LM (domain-tuned for PlutoClaw)
$ cd models/Pluto-LM-v4
$ ollama create plutoedge -f Modelfile
Clone the PlutoClaw repo first, then run from the models directory.
What it does
Edge-Optimized
Quantized for Apple Silicon, Raspberry Pi, and mobile SoCs. Runs in under 2GB RAM.
Privacy-First
All inference runs locally — zero cloud calls, zero data exposure.
PlutoClaw-Native
Designed to plug directly into PlutoClaw agent pipelines as the inference engine.
Open Source
Community-driven development with an open roadmap. Fork it, extend it, ship it.
Performance — what's fast and what's not
Reflex layer (skill & sensor loop)
0.22ms p95measured, Pi 4
Most skills poll sensors every 5–30s and fire actuators on threshold — this loop never calls the LLM. One skill (fire/smoke) also runs an event-driven GPIO path (edge-triggered, gpiozero/lgpio): measured p95 0.22ms / max 9.3ms over N=1000 on a Raspberry Pi 4. Not yet re-verified on Pi 5. Full numbers, caveats, and the reproducible script are in BENCHMARKS.md.
Reasoning layer (Pluto LM, Pi 4 CPU)
~37s
Pluto LM 1.5B reasoning per response on Raspberry Pi 4 CPU, 1024-token context, control-mode prompt. Used for decisions and Q&A — not time-critical sensor loops. Faster on Pi 5 or Mac.
Design principle: time-critical automation never waits on the LLM. The reflex layer acts immediately; Pluto LM judgment runs asynchronously, seconds later, only when needed.
Reproducible Benchmarks
Hardware, script, and measured p50/p95/max latency — one command to reproduce. See BENCHMARKS.md.
Research Paper
The Pluto LM 1.5B architecture, training methodology, and benchmark results will be published as a research paper.
Paper link coming soon