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Comparison

recurrentgemma vs oumi

Verdict

Pick recurrentgemma if recurrentGemma is an open-source language model from Google DeepMind, utilizing the Griffin architecture and supporting JAX and PyTorch for efficient neural network training and inference on TPUs, CPUs, and GPUs; 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 · recurrentgemma alternatives · oumi alternatives

GraphCanon updated Sep 20, 2026

16views this month

recurrentgemma logo

recurrentgemma

google-deepmind/recurrentgemma

★ 685pushed Feb 6, 2026
vs
oumi logo

oumi

oumi-ai/oumi

★ 9.4kpushed Sep 20, 2026

Trust & integrity

Signalrecurrentgemmaoumi
Maintenance
Slowing (212d since push)
As of Sep 6, 2026 · github_public_v1
Very active (0d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 6, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · 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
recurrentgemma trust reportoumi trust reportTrust methodology

Tagline

recurrentgemma
Open weights language model from Google DeepMind, based on Griffin
oumi
Easily fine-tune, evaluate and deploy open source LLMs/VLMs

Stars

recurrentgemma
685
oumi
9.4k

Forks

recurrentgemma
39
oumi
790

Open issues

recurrentgemma
4
oumi
34

Language

recurrentgemma
Python
oumi
Python

Adopt for

recurrentgemma
RecurrentGemma is an open-source language model from Google DeepMind, utilizing the Griffin architecture and supporting JAX and PyTorch for efficient neural network training and inference on TPUs, CPUs, and GPUs.
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

recurrentgemma
-
oumi
-

Runtime

recurrentgemma
-
oumi
-

License

recurrentgemma
The codebase is distributed under the permissive Apache License, version 2.0, allowing for broad usage but with no warranties expressed or implied.
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

recurrentgemma
Feb 6, 2026
oumi
Sep 20, 2026

Categories

recurrentgemma
Inference & Serving, Model Training
oumi
Evaluation & Observability, Inference & Serving, Model Training

Trust and health

Maintenance

recurrentgemma
Slowing (36%)
oumi
Very active (96%)

Days since push

recurrentgemma
212d
oumi
0d

Open issues (now)

recurrentgemma
4
oumi
34

Stars delta

recurrentgemma
+1 (30d)
oumi
+28 (30d)

Open issues delta

recurrentgemma
0 (30d)
oumi
+3 (30d)

Full report

recurrentgemma
Trust report
oumi
Trust report

Choose recurrentgemma if…

  • Requirements: Optimized for TPU using the Flax implementation.; Supports CPU and GPU environments via JAX and PyTorch..
  • Tags unique to recurrentgemma: deep-learning, flax, jax, language-model.
  • If you require high efficiency in neural network training or inferencing specifically optimized for TPUs using the Flax implementation

When NOT to use recurrentgemma

  • Do not use if your infrastructure does not support TensorFlow, since RecurrentGemma optimizes efficiency mostly on TPUs which are tightly coupled with TensorFlow's ecosystem
  • Avoid using this tool if you are working in a restricted environment where setting up virtual environments with tools like Poetry or manually managing dependencies with pip is challenging
GitHubDetails

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.
  • - 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).
GitHubDetails

Explore

recurrentgemma trust report →oumi trust report →Inference & Serving category →Model Training category →Evaluation & Observability category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: recurrentgemma 685 · oumi 9.4k (synced Sep 20, 2026).

Common questions

What is the difference between recurrentgemma and oumi?
recurrentgemma: Open weights language model from Google DeepMind, based on Griffin. 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 recurrentgemma over oumi?
Choose recurrentgemma over oumi when Requirements: Optimized for TPU using the Flax implementation.; Supports CPU and GPU environments via JAX and PyTorch.; Tags unique to recurrentgemma: deep-learning, flax, jax, language-model; If you require high efficiency in neural network training or inferencing specifically optimized for TPUs using the Flax implementation.
When should I choose oumi over recurrentgemma?
Choose oumi over recurrentgemma 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; - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants.
When should I avoid recurrentgemma?
Do not use if your infrastructure does not support TensorFlow, since RecurrentGemma optimizes efficiency mostly on TPUs which are tightly coupled with TensorFlow's ecosystem Avoid using this tool if you are working in a restricted environment where setting up virtual environments with tools like Poetry or manually managing dependencies with pip is challenging
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 recurrentgemma or oumi more popular on GitHub?
oumi has more GitHub stars (9,387 vs 685). Stars measure visibility, not whether either tool fits your constraints.
Are recurrentgemma and oumi open source?
Yes - both are open-source projects on GitHub (recurrentgemma: Apache-2.0, oumi: Apache-2.0).
Where can I find alternatives to recurrentgemma or oumi?
GraphCanon lists graph-backed alternatives at recurrentgemma alternatives and oumi alternatives (recurrentgemma 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, recurrentgemma or oumi?
recurrentgemma: 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 recurrentgemma and oumi?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: recurrentgemma trust report; oumi trust report.

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