Hope its a cool local LLM.

Also will soon have this running on RP2350 soon, so stay tuned for that!

picoClaw has a built in provider router to that heartbeats etc can go local to save tokens and $$$

eg

  "providers": {
    "default": {
      "api_key": "",
      "base_url": "https://api.openai.com/v1",
      "model": "gpt-4o-mini",
      "type": "chat",
      "cost": { "input": 0.15, "output": 0.60 }
    },
    "gemini": {
      "api_key": "",
      "base_url": "https://generativelanguage.googleapis.com/v1beta/openai",
      "model": "gemini-3.1-pro-preview",
      "type": "chat",
      "cost": { "input": 0.15, "output": 0.60 }
    },
    "fast": {
      "api_key": "",
      "base_url": "https://generativelanguage.googleapis.com/v1beta/openai",
      "model": "gemini-2.0-flash-lite",
      "type": "chat",
      "cost": { "input": 0.075, "output": 0.30 }
    },
    "local": {
      "base_url": "http://192.168.1.238:1337/v1",
      "model": "gemma-3n-e4b-it-lm-4bit",
      "type": "chat",
      "tools": false,
      "context_window": 4096,
      "cost": { "input": 0, "output": 0 }
    },
    "image": {
      "api_key": "",
      "base_url": "https://generativelanguage.googleapis.com/v1beta",
      "model": "gemini-3-pro-image-preview",
      "type": "image"
    }
  },
  "routing": {
    "heartbeat": "default",
    "cron": "default",
    "chat": "default",
    "subagent": "default",
    "monthly_budget_usd": 5.0,
    "warn_at_pct": 80,
    "throttle_at_pct": 95,
    "throttle_to": "default"
  },
  "channels": {
    "telegram": {
      "enabled": false,
      "bot_token": "",
      "default_chat_id": ""
    }
  },
  "memory": {
    "vector_weight": 0.7,
    "text_weight": 0.3,
    "min_score": 0.35,
    "max_result_chars": 2000,
    "max_results": 5,
    "chunk_size": 400,
    "chunk_overlap": 80,
    "reindex_on_boot": true,
    "embedding_cache": true,
    "embedding_provider": "openai",
    "embed_async": true
  },
  "compaction": {
    "context_window": 128000,
    "reserve_tokens": 4000,
    "history_share": 0.6
  },
  "memory_flush": {
    "enabled": true,
    "soft_threshold_tokens": 4000,
    "force_flush_transcript_bytes": 65536,
    "prompt": "",
    "system_prompt": ""
  },
  "temperature": {
    "heartbeat": 0.9,
    "reflection": 1
  },

As a robot it literally can program itself; it becomes its own firmware engineer, and can adapt its own code.

As an assistant, it remembers everything, up to the limit of its 2TB sdcard, both facts and vectors, but can still reach out to say Google sheets.

As a plaything , it's a tamagotchi on steroids with it own character that responds to voice.

---

Lets say you had an unknown EV motor on a CAN bus. You want to make it run, but you don’t now the right protocols, or the right codes. An LLM does, or can work it out. You ask the device, as you would ask an experienced firmware engineer, play with this motor until you make it work. So the LLM does, and when it has the code working, it creates a skill that runs the motor when a pedal on CAN bus is pressed. No more firmware engineer.

Or lets say you want to build a wearable that runs on batteries for a long time, so need a mW class processor that can store all your context, and goes with you everywhere, the pendant, the clasp, the buckle. You speak to it with your earbuds, it only knows wake words but streams your audio to the LLM. Its not just a chat bot. It is the agent that stores your whole digital life .

Or maybe, because it’s a $2 part, it’s whimsical, like a tamagotchi or a bag charm. Take care of me and I respond, but I help you too. ‘You tell stuff to me you don’t want to tell Google or Apple, or even your best friend’.

---

The key is this is not a chat bot, it’s an embodied OpenClaw class agent, take it where you will, on whatever LLM you will. And it’s so cheap, you can tie it to your service and give it away.

As for speed, ask yourself, how does numpy work? The answer to that is exactly why pycoClaw works. Its 20K LOC fast path is in C , but it’s exposed to the Agent as Python, because it has to be. It has to be run time modifiable, because thats what an agent needs, because an agent is ‘just’ a while loop with a REPL. The key is what the LLM populates the REPL with.

The LLM is the tokens in, tokens out intelligence, but it turns out the Agent or Harness is where the power really lies.

pycoClaw is the LLM harness for hardware.