Comparison
open-r1 vs oumi
Verdict
Pick open-r1 if open-R1 is an open-source effort to replicate DeepSeek-R1's models and training pipelines involving model distillation, RL pipeline replication, and multi-stage training; pick oumi if oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others.
Markdown twin · open-r1 alternatives · oumi alternatives
GraphCanon updated 2d
Trust & integrity
| Signal | open-r1 | oumi |
|---|---|---|
| Maintenance | Slowing (125d since push) As of 2w · github_public_v1 | Very active (1d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- open-r1
- Fully open reproduction of DeepSeek-R1
- oumi
- Easily fine-tune, evaluate and deploy open source LLMs/VLMs
Stars
- open-r1
- 26k
- oumi
- 9.4k
Forks
- open-r1
- 2.4k
- oumi
- 784
Open issues
- open-r1
- 340
- oumi
- 34
Language
- open-r1
- Python
- oumi
- Python
Adopt for
- open-r1
- Open-R1 is an open-source effort to replicate DeepSeek-R1's models and training pipelines involving model distillation, RL pipeline replication, and multi-stage training.
- oumi
- Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others.
Persona
- open-r1
- -
- oumi
- -
Runtime
- open-r1
- -
- oumi
- -
License
- open-r1
- The project is licensed under Apache-2.0, providing a permissive license that allows for free use, modification, and distribution.
- oumi
- Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues.
Last pushed
- open-r1
- Apr 2, 2026
- oumi
- Aug 21, 2026
Categories
- open-r1
- Inference & Serving, Model Training
- oumi
- Evaluation & Observability, Inference & Serving, Model Training
Trust and health
Maintenance
- open-r1
- Slowing (36%)
- oumi
- Very active (96%)
Days since push
- open-r1
- 125d
- oumi
- 1d
Open issues (now)
- open-r1
- 340
- oumi
- 34
Stars delta
- open-r1
- Unknown
- oumi
- +17 (30d)
Open issues delta
- open-r1
- Unknown
- oumi
- +3 (30d)
Full report
- open-r1
- Trust report
- oumi
- Trust report
Choose open-r1 if…
- Requirements: Min 8 GB RAM; Installation requires CUDA version 12.4 and PyTorch v2.6.0, with specific dependencies like vLLM and FlashAttention that are critical..
- Tags unique to open-r1: cuda, deepseek-r1, flashattention, model distillation.
- Use Open-R1 when you need a detailed understanding of how DeepSeek-R1 operates, considering the project closely mirrors its architecture and processes.
When NOT to use open-r1
- Avoid Open-R1 if your hardware does not support CUDA 12.4 or cannot run PyTorch `v2.6.0`, as this may lead to errors.
- Do not use it if the need for rapid experimentation outweighs the value of detailed replication, since the multi-stage training and datasets curation process can be time-consuming.
Choose oumi if…
- Requirements: Requires Docker; Docker is used for standardized and portable environment deployments..
- Tags unique to oumi: dpo, evaluation, fine-tuning, llms.
- Also covers Evaluation & Observability.
- oumi ships Docker support for self-hosted deployment.
- - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants.
When NOT to use oumi
- - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations.
- - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series).
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (huggingface/open-r1) · observed Aug 6, 2026
- GitHub forks (huggingface/open-r1) · observed Aug 6, 2026
- Last push (huggingface/open-r1) · observed Apr 2, 2026
- License file (Apache-2.0) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (oumi-ai/oumi) · observed Aug 23, 2026
- GitHub forks (oumi-ai/oumi) · observed Aug 23, 2026
- Last push (oumi-ai/oumi) · observed Aug 21, 2026
- License file (Apache-2.0) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: open-r1 26k · oumi 9.4k (synced Aug 6, 2026).
Common questions
- What is the difference between open-r1 and oumi?
- open-r1: Fully open reproduction of DeepSeek-R1. oumi: Easily fine-tune, evaluate and deploy open source LLMs/VLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose open-r1 over oumi?
- Choose open-r1 over oumi when Requirements: Min 8 GB RAM; Installation requires CUDA version 12.4 and PyTorch v2.6.0, with specific dependencies like vLLM and FlashAttention that are critical.; Tags unique to open-r1: cuda, deepseek-r1, flashattention, model distillation; Use Open-R1 when you need a detailed understanding of how DeepSeek-R1 operates, considering the project closely mirrors its architecture and processes.
- When should I choose oumi over open-r1?
- Choose oumi over open-r1 when Requirements: Requires Docker; Docker is used for standardized and portable environment deployments.; Tags unique to oumi: dpo, evaluation, fine-tuning, llms; Also covers Evaluation & Observability; oumi ships Docker support for self-hosted deployment; - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants.
- When should I avoid open-r1?
- Avoid Open-R1 if your hardware does not support CUDA 12.4 or cannot run PyTorch
v2.6.0, as this may lead to errors. Do not use it if the need for rapid experimentation outweighs the value of detailed replication, since the multi-stage training and datasets curation process can be time-consuming. - When should I avoid oumi?
- - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations. - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series).
- Is open-r1 or oumi more popular on GitHub?
- open-r1 has more GitHub stars (26,423 vs 9,376). Stars measure visibility, not whether either tool fits your constraints.
- Are open-r1 and oumi open source?
- Yes - both are open-source projects on GitHub (open-r1: Apache-2.0, oumi: Apache-2.0).
- Where can I find alternatives to open-r1 or oumi?
- GraphCanon lists graph-backed alternatives at open-r1 alternatives and oumi alternatives (open-r1 markdown twin, oumi markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, open-r1 or oumi?
- open-r1: Slowing. oumi: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for open-r1 and oumi?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: open-r1 trust report; oumi trust report.