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logxio/picchio

Analysis updated 2026-05-18

17PythonAudience · developerComplexity · 3/5LicenseSetup · easy

TLDR

A single-file Python tool that catches when a local LLM is silently running on CPU instead of GPU, or has a mislabeled quantization.

Mindmap

mindmap
  root((picchio))
    What it does
      Diagnoses local LLM speed
      Catches CPU fallback
      Verifies quant labels
    Tech stack
      Python
      llama.cpp
      Ollama
    Use cases
      Detect silent CPU fallback
      Monitor a running model server
      Compare diagnostic results
    Audience
      Developers
      Local LLM tinkerers
      AI tool builders

Code map

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What do people build with it?

USE CASE 1

Check whether a local LLM is silently running on CPU instead of the GPU

USE CASE 2

Verify that a quantized model file matches its label before trusting benchmark numbers

USE CASE 3

Monitor a running llama.cpp or Ollama server over time for GPU fallback

USE CASE 4

Compare two saved diagnostic results to find what config change caused a slowdown

What is it built with?

Pythonllama.cppOllama

How does it compare?

logxio/picchio0petru/sentimoalingalingling/akasha-wechat
Stars171717
LanguagePythonPythonPython
Setup difficultyeasymoderatehard
Complexity3/53/54/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

One curl download plus a local llama.cpp or Ollama install, no other dependencies.

Use, modify, and redistribute the code freely, including commercially, as long as you keep the copyright notice.

In plain English

picchio is a single Python file that checks whether a locally running large language model is actually using your GPU the way you think it is. Many tools report a single tokens per second number, and that number can be technically correct while still hiding a real problem, such as the model quietly falling back to running on the CPU instead of the GPU, or a quantized model file being labeled the same as another file that is actually a different size in memory. picchio catches these kinds of mismatches by running the model several times, splitting the timing into separate stages such as reading the prompt and generating new text, and comparing what the model runtime reports against what the operating system's own GPU usage monitor reports. It works with two popular ways of running local models, llama.cpp and Ollama, and needs Python 3 plus one of those two already installed. Running it with no extra options makes it search for models you already have, whether from Ollama, a Hugging Face cache, an LM Studio cache, or the current folder, and lets you pick one to test. Pointing it directly at a model file gives a full diagnosis with three timed passes, while pointing it at an already running server measures that server without starting anything new. Beyond basic diagnosis, picchio includes commands for watching GPU activity over time next to a process you are running, monitoring a running model server on a repeating timer to catch it losing GPU access partway through, comparing two saved diagnostic results side by side to see what changed, and verifying whether a pasted diagnostic result is internally consistent or looks tampered with. It also prints a stable, machine readable output format meant for AI coding assistants like Codex or Claude Code to call directly. The tool writes only a single small cache file to your computer and otherwise leaves no other trace. It is released under the MIT license and the whole project is one downloadable file, though its source code is organized into normal modules for anyone who wants to read or modify it.

Copy-paste prompts

Prompt 1
Help me install picchio and run a full diagnosis on my local GGUF model
Prompt 2
Explain what picchio's prefill and decode lanes mean and why they can disagree
Prompt 3
Show me how to use picchio watch to monitor GPU usage next to my Ollama model
Prompt 4
Walk me through comparing two picchio verdict blocks to find what changed

Frequently asked questions

What is picchio?

A single-file Python tool that catches when a local LLM is silently running on CPU instead of GPU, or has a mislabeled quantization.

What language is picchio written in?

Mainly Python. The stack also includes Python, llama.cpp, Ollama.

What license does picchio use?

Use, modify, and redistribute the code freely, including commercially, as long as you keep the copyright notice.

How hard is picchio to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is picchio for?

Mainly developer.

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