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Comparison

BodhiApp vs fastDeploy

Verdict

Pick BodhiApp if bodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods; pick fastDeploy if fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines.

Markdown twin · BodhiApp alternatives · fastDeploy alternatives

GraphCanon updated Sep 20, 2026

18views this month

BodhiApp logo

BodhiApp

BodhiSearch/BodhiApp

★ 139pushed Sep 20, 2026
vs
fastDeploy logo

fastDeploy

notAI-tech/fastDeploy

★ 105pushed Feb 10, 2026

Trust & integrity

SignalBodhiAppfastDeploy
Maintenance
Very active (0d since push)
As of Sep 20, 2026 · github_public_v1
Slowing (221d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 20, 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 15, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 15, 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
BodhiApp trust reportfastDeploy trust reportTrust methodology

Tagline

BodhiApp
Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs
fastDeploy
Deploy DL/ML inference pipelines with minimal extra code.

Stars

BodhiApp
139
fastDeploy
105

Forks

BodhiApp
11
fastDeploy
17

Open issues

BodhiApp
12
fastDeploy
0

Language

BodhiApp
TypeScript
fastDeploy
Python

Adopt for

BodhiApp
BodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods.
fastDeploy
fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines.

Persona

BodhiApp
-
fastDeploy
-

Runtime

BodhiApp
-
fastDeploy
-

License

BodhiApp
The license information for BodhiApp has not been provided.
fastDeploy
MIT

Last pushed

BodhiApp
Sep 20, 2026
fastDeploy
Feb 10, 2026

Categories

BodhiApp
Inference & Serving, LLM Frameworks
fastDeploy
Inference & Serving

Trust and health

Maintenance

BodhiApp
Very active (96%)
fastDeploy
Slowing (36%)

Days since push

BodhiApp
0d
fastDeploy
221d

Open issues (now)

BodhiApp
12
fastDeploy
0

Stars delta

BodhiApp
+3 (30d)
fastDeploy
0 (30d)

Open issues delta

BodhiApp
+2 (30d)
fastDeploy
0 (30d)

Full report

BodhiApp
Trust report
fastDeploy
Trust report

Choose BodhiApp if…

  • BodhiApp is primarily TypeScript; fastDeploy is Python.
  • Pricing: Pricing details are not mentioned in the repository data..
  • Requirements: Requires Docker; Requires Docker environment. Specific model requirements vary depending on the hardware variant chosen..
  • Tags unique to BodhiApp: gemma, generative-ai, llama, llm.
  • Also covers LLM Frameworks.
  • You need to deploy LLMs locally with flexible hardware support including AMD, NVIDIA GPUs, and CPUs.

When NOT to use BodhiApp

  • Your project strictly requires non-local deployment options, as BodhiApp focuses on local hosting of models.
  • If your environment is limited to unsupported GPU hardware or lacks adequate drivers for CUDA, ROCm, or Vulkan acceleration methods.
  • You need support beyond Mac platforms as BodhiApp does not yet provide installation instructions for other operating systems.
GitHubDetails

Choose fastDeploy if…

  • fastDeploy is primarily Python; BodhiApp is TypeScript.
  • Pricing: -.
  • Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory..
  • Tags unique to fastDeploy: deep-learning, docker, falcon, gevent.
  • When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding.

When NOT to use fastDeploy

  • Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability.
  • Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations.
GitHubDetails

Explore

BodhiApp trust report →fastDeploy trust report →Inference & Serving category →LLM Frameworks 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: BodhiApp 139 · fastDeploy 105 (synced Sep 20, 2026).

Common questions

What is the difference between BodhiApp and fastDeploy?
BodhiApp: Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs. fastDeploy: Deploy DL/ML inference pipelines with minimal extra code.. See the comparison table for live GitHub stats and shared categories.
When should I choose BodhiApp over fastDeploy?
Choose BodhiApp over fastDeploy when BodhiApp is primarily TypeScript; fastDeploy is Python; Pricing: Pricing details are not mentioned in the repository data.; Requirements: Requires Docker; Requires Docker environment. Specific model requirements vary depending on the hardware variant chosen.; Tags unique to BodhiApp: gemma, generative-ai, llama, llm; Also covers LLM Frameworks; You need to deploy LLMs locally with flexible hardware support including AMD, NVIDIA GPUs, and CPUs.
When should I choose fastDeploy over BodhiApp?
Choose fastDeploy over BodhiApp when fastDeploy is primarily Python; BodhiApp is TypeScript; Pricing: -; Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.; Tags unique to fastDeploy: deep-learning, docker, falcon, gevent; When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding.
When should I avoid BodhiApp?
Your project strictly requires non-local deployment options, as BodhiApp focuses on local hosting of models. If your environment is limited to unsupported GPU hardware or lacks adequate drivers for CUDA, ROCm, or Vulkan acceleration methods. You need support beyond Mac platforms as BodhiApp does not yet provide installation instructions for other operating systems.
When should I avoid fastDeploy?
Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability. Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations.
Is BodhiApp or fastDeploy more popular on GitHub?
BodhiApp has more GitHub stars (139 vs 105). Stars measure visibility, not whether either tool fits your constraints.
Are BodhiApp and fastDeploy open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to BodhiApp or fastDeploy?
GraphCanon lists graph-backed alternatives at BodhiApp alternatives and fastDeploy alternatives (BodhiApp markdown twin, fastDeploy 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, BodhiApp or fastDeploy?
BodhiApp: Very active. fastDeploy: Slowing. 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 BodhiApp and fastDeploy?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: BodhiApp trust report; fastDeploy trust report.

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