Comparison
BodhiApp vs mlx-serve
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 mlx-serve if focused on supporting Apple Silicon-powered macOS devices, mlx-serve provides a native and API-compatible inference service without requiring Python.
Markdown twin · BodhiApp alternatives · mlx-serve alternatives
GraphCanon updated Sep 20, 2026
14views this month
vs
Trust & integrity
| Signal | BodhiApp | mlx-serve |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 20, 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 20, 2026 · github_public_v1 | Not a fork · Personal 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 |
Tagline
- BodhiApp
- Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs
- mlx-serve
- Native LLM inference server for Apple Silicon
Stars
- BodhiApp
- 139
- mlx-serve
- 1.4k
Forks
- BodhiApp
- 11
- mlx-serve
- 130
Open issues
- BodhiApp
- 12
- mlx-serve
- 54
Language
- BodhiApp
- TypeScript
- mlx-serve
- Zig
Adopt for
- BodhiApp
- BodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods.
- mlx-serve
- Focused on supporting Apple Silicon-powered macOS devices, mlx-serve provides a native and API-compatible inference service without requiring Python.
Persona
- BodhiApp
- -
- mlx-serve
- -
Runtime
- BodhiApp
- -
- mlx-serve
- -
License
- BodhiApp
- The license information for BodhiApp has not been provided.
- mlx-serve
- MIT
Last pushed
- BodhiApp
- Sep 20, 2026
- mlx-serve
- Sep 19, 2026
Categories
- BodhiApp
- Inference & Serving, LLM Frameworks
- mlx-serve
- Inference & Serving
Trust and health
Open issues (now)
- BodhiApp
- 12
- mlx-serve
- 54
Stars delta
- BodhiApp
- +3 (30d)
- mlx-serve
- +1.1k (30d)
Open issues delta
- BodhiApp
- +2 (30d)
- mlx-serve
- +51 (30d)
Owner type
- BodhiApp
- Organization
- mlx-serve
- User
Full report
- BodhiApp
- Trust report
- mlx-serve
- Trust report
Choose BodhiApp if…
- BodhiApp is primarily TypeScript; mlx-serve is Zig.
- 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.
Choose mlx-serve if…
- mlx-serve is primarily Zig; BodhiApp is TypeScript.
- Requirements: Requires Apple Silicon-powered macOS devices to ensure optimal performance and compatibility..
- Tags unique to mlx-serve: agent, anthropic-api, apple-silicon, deepseek-v4.
- Use when your project requires running large language model (LLM) inferencing natively on Apple Silicon hardware.
When NOT to use mlx-serve
- Avoid if your infrastructure does not include devices with Apple Silicon chips, as it is specifically optimized for this architecture.
- Do not use if you require cross-platform compatibility as mlx-serve targets macOS exclusively.
- This tool might not be suitable if Python integration is crucial in your project.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (BodhiSearch/BodhiApp) · observed Sep 20, 2026
- GitHub forks (BodhiSearch/BodhiApp) · observed Sep 20, 2026
- Last push (BodhiSearch/BodhiApp) · observed Sep 20, 2026
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (ddalcu/mlx-serve) · observed Sep 20, 2026
- GitHub forks (ddalcu/mlx-serve) · observed Sep 20, 2026
- Last push (ddalcu/mlx-serve) · observed Sep 19, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: BodhiApp 139 · mlx-serve 1.4k (synced Sep 20, 2026).
Common questions
- What is the difference between BodhiApp and mlx-serve?
- BodhiApp: Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs. mlx-serve: Native LLM inference server for Apple Silicon. See the comparison table for live GitHub stats and shared categories.
- When should I choose BodhiApp over mlx-serve?
- Choose BodhiApp over mlx-serve when BodhiApp is primarily TypeScript; mlx-serve is Zig; 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 mlx-serve over BodhiApp?
- Choose mlx-serve over BodhiApp when mlx-serve is primarily Zig; BodhiApp is TypeScript; Requirements: Requires Apple Silicon-powered macOS devices to ensure optimal performance and compatibility.; Tags unique to mlx-serve: agent, anthropic-api, apple-silicon, deepseek-v4; Use when your project requires running large language model (LLM) inferencing natively on Apple Silicon hardware.
- 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 mlx-serve?
- Avoid if your infrastructure does not include devices with Apple Silicon chips, as it is specifically optimized for this architecture. Do not use if you require cross-platform compatibility as mlx-serve targets macOS exclusively. This tool might not be suitable if Python integration is crucial in your project.
- Is BodhiApp or mlx-serve more popular on GitHub?
- mlx-serve has more GitHub stars (1,418 vs 139). Stars measure visibility, not whether either tool fits your constraints.
- Are BodhiApp and mlx-serve open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to BodhiApp or mlx-serve?
- GraphCanon lists graph-backed alternatives at BodhiApp alternatives and mlx-serve alternatives (BodhiApp markdown twin, mlx-serve 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 mlx-serve?
- BodhiApp: Very active. mlx-serve: 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 BodhiApp and mlx-serve?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: BodhiApp trust report; mlx-serve trust report.