TinyZero logo

TinyZero

Jiayi-Pan/TinyZero

Minimal reproduction of DeepSeek R1-Zero

GraphCanon updated Oct 10, 2026 · GitHub synced Oct 10, 2026

38views this month

13k stars1.6k forksLast push Feb 27, 2026 Python Apache-2.0

Decision brief

TinyZero is a scaled-down version of the R1-Zero architecture from DeepSeek, focusing on minimal setup with essential components.

Good fit when

  • When you need a streamlined implementation of the R1-Zero architecture without unnecessary complexity.
  • For projects that require leveraging vLLM and Ray for efficient processing but prefer a lightweight framework setup.

Avoid when

  • If your project demands extensive customization options not available in this minimal version.
  • When working with environments where specific versions of PyTorch older than 2.4.0 are required, as TinyZero mandates the use of PyTorch 2.4.0 or allows vLLM to manage its installation.
Pricing:
freemium - The framework itself is free and can be used without charge;
Requirements:
Min 4 GB RAM; Specific Python environment setup (Python 3.9) and dependency installation steps are outlined in the README.

Observed Jul 11, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Slowing (225d since push)
As of Oct 10, 2026
Provenance
Not a fork · Personal account
As of Oct 10, 2026
Security (OSV)
No criticals
As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install TinyZero
PyPI

How it fits your stack(1)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A minimal version of the R1-Zero architecture from DeepSeek, setup instructions provided in README for environment creation and dependencies installation including vLLM and Ray.

Capability facts

Languages
python

Source: github.language+pyproject.toml · Oct 10, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Oct 10, 2026)

conda create -n zero python=3.9
Source link

Tags

README

Installation ``` conda create n zero python=3.9 install torch [or you can skip this step and let vllm install the correct version for you] pip install torch==2.4.0 index url https://download.pytorch.org/whl/cu121 install vllm pip3 install vllm==0.6.3 or you can install 0.5.4, 0.4...

For agents

This page has a .md twin and JSON over the API.

Was this helpful?

Anonymous feedback helps us improve pages and translations.