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Comparison

optillm vs optimate

Verdict

Pick optillm if optillm is an optimizing inference proxy for LLMs that provides enhanced deployment options through Docker, supporting both full and lightweight configurations; pick optimate if optiMate is a legacy collection of Python libraries for optimizing AI models, including Speedster for inference cost reduction, Nos for infrastructure cost reduction, and ChatLLaMA for hardware and data cost reduction.

Markdown twin · optillm alternatives · optimate alternatives

GraphCanon updated Sep 20, 2026

9views this month

optillm logo

optillm

algorithmicsuperintelligence/optillm

★ 4.2kpushed Jul 18, 2026
vs
optimate logo

optimate

nebuly-ai/optimate

★ 8.3kpushed Jul 22, 2024

Trust & integrity

Signaloptillmoptimate
Maintenance
Steady (30d since push)
As of Aug 17, 2026 · github_public_v1
Dormant (788d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Aug 17, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
Published findings
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Sep 18, 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

Tagline

optillm
Optimizing inference proxy for LLMs
optimate
A collection of libraries to optimise AI model performances

Stars

optillm
4.2k
optimate
8.3k

Forks

optillm
385
optimate
613

Open issues

optillm
25
optimate
109

Language

optillm
Python
optimate
Python

Adopt for

optillm
optillm is an optimizing inference proxy for LLMs that provides enhanced deployment options through Docker, supporting both full and lightweight configurations.
optimate
OptiMate is a legacy collection of Python libraries for optimizing AI models, including Speedster for inference cost reduction, Nos for infrastructure cost reduction, and ChatLLaMA for hardware and data cost reduction.

Persona

optillm
-
optimate
-

Runtime

optillm
-
optimate
-

License

optillm
Apache-2.0
optimate
OptiMate is licensed under Apache-2.0, allowing for free use, modification, and distribution.

Last pushed

optillm
Jul 18, 2026
optimate
Jul 22, 2024

Categories

optillm
Inference & Serving
optimate
Inference & Serving, Model Training

Trust and health

Maintenance

optillm
Steady (60%)
optimate
Dormant (18%)

Days since push

optillm
30d
optimate
788d

Open issues (now)

optillm
25
optimate
109

Stars delta

optillm
+67 (30d)
optimate
-1 (30d)

Open issues delta

optillm
+5 (30d)
optimate
-1 (30d)

OSV dependency advisories

optillm
Published findings
optimate
No lockfile (source not queried)

Full report

optimate
Trust report

Choose optillm if…

  • This open-source proxy supports diverse hosting environments and can be run via Docker for flexibility in deployment.
  • Pricing: optillm is available under the Apache-2.0 license, which makes it free to use and distribute without cost..
  • Tags unique to optillm: agent, agentic-ai, genai, llm-inference.
  • optillm ships Docker support for self-hosted deployment.
  • Use optillm when you require automatic optimization of the server approach to enhance reasoning capabilities with large language models.

When NOT to use optillm

  • Avoid optillm when your application does not require proxy server optimization for large language models; simpler serving setups may suffice.
  • Do not use optillm if your deployment environment strictly prohibits the use of Docker images or containers, given that this tool heavily relies on Docker for its various configurations.

Choose optimate if…

  • Requirements: OptiMate is a legacy project and no longer actively maintained, so users should be prepared to handle any issues without official support..
  • Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning.
  • Also covers Model Training.
  • When you need to leverage legacy optimization techniques for reducing inference costs with Speedster, infrastructure costs with Nos, and hardware and data costs with ChatLLaMA.

When NOT to use optimate

  • If you require the latest optimization techniques and ongoing support, as OptiMate is in a legacy phase and no longer actively maintained.
  • When you need to integrate with modern AI frameworks that require the latest updates and patches, as OptiMate does not receive these updates.

Explore

Sources

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

GitHub stars on cards: optillm 4.2k · optimate 8.3k (synced Sep 20, 2026).

Common questions

What is the difference between optillm and optimate?
optillm: Optimizing inference proxy for LLMs. optimate: A collection of libraries to optimise AI model performances. See the comparison table for live GitHub stats and shared categories.
When should I choose optillm over optimate?
Choose optillm over optimate when This open-source proxy supports diverse hosting environments and can be run via Docker for flexibility in deployment; Pricing: optillm is available under the Apache-2.0 license, which makes it free to use and distribute without cost.; Tags unique to optillm: agent, agentic-ai, genai, llm-inference; optillm ships Docker support for self-hosted deployment; Use optillm when you require automatic optimization of the server approach to enhance reasoning capabilities with large language models.
When should I choose optimate over optillm?
Choose optimate over optillm when Requirements: OptiMate is a legacy project and no longer actively maintained, so users should be prepared to handle any issues without official support.; Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning; Also covers Model Training; When you need to leverage legacy optimization techniques for reducing inference costs with Speedster, infrastructure costs with Nos, and hardware and data costs with ChatLLaMA.
When should I avoid optillm?
Avoid optillm when your application does not require proxy server optimization for large language models; simpler serving setups may suffice. Do not use optillm if your deployment environment strictly prohibits the use of Docker images or containers, given that this tool heavily relies on Docker for its various configurations.
When should I avoid optimate?
If you require the latest optimization techniques and ongoing support, as OptiMate is in a legacy phase and no longer actively maintained. When you need to integrate with modern AI frameworks that require the latest updates and patches, as OptiMate does not receive these updates.
Is optillm or optimate more popular on GitHub?
optimate has more GitHub stars (8,328 vs 4,244). Stars measure visibility, not whether either tool fits your constraints.
Are optillm and optimate open source?
Yes - both are open-source projects on GitHub (optillm: Apache-2.0, optimate: Apache-2.0).
Where can I find alternatives to optillm or optimate?
GraphCanon lists graph-backed alternatives at optillm alternatives and optimate alternatives (optillm markdown twin, optimate 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, optillm or optimate?
optillm: Steady. optimate: Dormant. 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 optillm and optimate?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: optillm trust report; optimate trust report.

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