# GAIR-NLP/O1-Journey

O1 Replication Journey

Repository: https://github.com/GAIR-NLP/O1-Journey
Canonical: https://ross.abutalabs.com/products/o1-journey
License Family: other
Last push: 2025-01-14T04:32:18+00:00

## Health v2 (maintenance only)
Score: 22/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 1, release rhythm 35, longevity 49
- inputs: {"age_days": 695, "days_push": 596, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2002, forks 61 (observed 2026-08-28T04:06:04.414529+00:00)

## What it is
A research project and report series from GAIR at Shanghai Jiao Tong University documenting the journey of replicating OpenAI's O1 reasoning model, including studies on distillation and inference-time scaling. It serves primarily as a collection of technical reports and findings rather than production software.

## Use cases
- understand how to replicate o1-style reasoning in llms
- learn about o1 distillation techniques
- study inference-time scaling for reasoning
- research deep thinking in medical diagnosis with llms
- follow academic reports on reasoning model training

## When to choose
- you are researching o1 replication and reasoning model training
- you want technical reports on distillation and inference-time scaling
- you need academic insights into llm reasoning behaviors

## When to avoid
- you need production-ready training code or a maintained library
- you want a turnkey tool rather than research reports
- you need licensed, supported software for commercial use

## Facets
- artifact type: learning-resource
- maturity: active
- function: llm-training, machine-learning, llm-inference
- domain: large-language-models, artificial-intelligence, tutorials
- platform: python
- tags: research, o1-replication, reasoning, reinforcement-learning, academic-paper

## Member repositories
- GAIR-NLP/O1-Journey (main) score 22

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:04.414529+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:01:56.154993+00:00, confidence not recorded.
  - readme: https://github.com/GAIR-NLP/O1-Journey (fetched 2026-08-28T04:06:04.414529+00:00, sha 966734189e4c)
- Data as of 2026-08-30T08:39:29.467469+00:00.