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Home/Compare/lmdeploy vs aikit

Comparison

lmdeploy vs aikit

Verdict

Pick lmdeploy when lmdeploy is primarily Python; aikit is Go; pick aikit when aikit is primarily Go; lmdeploy is Python.

Markdown twin · lmdeploy alternatives · aikit alternatives

GraphCanon updated today

lmdeploy logo

lmdeploy

InternLM/lmdeploy

★ 8.0kpushed Jul 10, 2026
vs
aikit logo

aikit

kaito-project/aikit

★ 533pushed Jul 11, 2026

Trust & integrity

Signallmdeployaikit
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
lmdeploy trust reportaikit trust reportTrust methodology

Tagline

lmdeploy
LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
aikit
Fine-tune, build, and deploy open-source LLMs easily!

Stars

lmdeploy
8.0k
aikit
533

Forks

lmdeploy
703
aikit
57

Open issues

lmdeploy
597
aikit
41

Language

lmdeploy
Python
aikit
Go

Adopt for

lmdeploy
-
aikit
Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies.

Persona

lmdeploy
-
aikit
-

Runtime

lmdeploy
-
aikit
-

License

lmdeploy
Apache-2.0
aikit
MIT

Last pushed

lmdeploy
Jul 10, 2026
aikit
Jul 11, 2026

Categories

lmdeploy
LLM Frameworks, Model Training, Inference & Serving
aikit
LLM Frameworks, Model Training, Inference & Serving

Trust and health

Open issues (now)

lmdeploy
597
aikit
41

Full report

lmdeploy
Trust report
aikit
Trust report

Choose lmdeploy if…

  • lmdeploy is primarily Python; aikit is Go.
  • License: lmdeploy is Apache-2.0, aikit is MIT.
  • Tags unique to lmdeploy: codellama, llama, deepspeed, fastertransformer.

When NOT to use lmdeploy

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Choose aikit if…

  • aikit is primarily Go; lmdeploy is Python.
  • License: aikit is MIT, lmdeploy is Apache-2.0.
  • Tags unique to aikit: gemma, fine-tuning, ai, docker.
  • aikit ships Docker support for self-hosted deployment.
  • - You need a flexible solution specifically built using Go and prefer its concurrency model.

When NOT to use aikit

  • - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit.
  • - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these.
GitHubDetails

Explore

lmdeploy trust report →aikit trust report →LLM Frameworks category →Model Training category →Inference & Serving 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: lmdeploy 8.0k · aikit 533 (synced Jul 11, 2026).

Common questions

What is the difference between lmdeploy and aikit?
lmdeploy: LMDeploy is a toolkit for compressing, deploying, and serving LLMs.. aikit: Fine-tune, build, and deploy open-source LLMs easily!. See the comparison table for live GitHub stats and shared categories.
When should I choose lmdeploy over aikit?
Choose lmdeploy over aikit when lmdeploy is primarily Python; aikit is Go; License: lmdeploy is Apache-2.0, aikit is MIT; Tags unique to lmdeploy: codellama, llama, deepspeed, fastertransformer.
When should I choose aikit over lmdeploy?
Choose aikit over lmdeploy when aikit is primarily Go; lmdeploy is Python; License: aikit is MIT, lmdeploy is Apache-2.0; Tags unique to aikit: gemma, fine-tuning, ai, docker; aikit ships Docker support for self-hosted deployment; - You need a flexible solution specifically built using Go and prefer its concurrency model.
When should I avoid lmdeploy?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
When should I avoid aikit?
- You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these.
Is lmdeploy or aikit more popular on GitHub?
lmdeploy has more GitHub stars (7,952 vs 533). Stars measure visibility, not whether either tool fits your constraints.
Are lmdeploy and aikit open source?
Yes - both are open-source projects on GitHub (lmdeploy: Apache-2.0, aikit: MIT).
Where can I find alternatives to lmdeploy or aikit?
GraphCanon lists graph-backed alternatives at lmdeploy alternatives and aikit alternatives (lmdeploy markdown twin, aikit 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, lmdeploy or aikit?
lmdeploy: Very active. aikit: 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 lmdeploy and aikit?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lmdeploy trust report; aikit trust report.