Comparison
LLM.swift vs airllm
Verdict
Pick LLM.swift if lLM.swift is a cross-platform C++ library for Apple systems that simplifies local interaction with large language models; pick airllm if airLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI.
Markdown twin · LLM.swift alternatives · airllm alternatives
GraphCanon updated Sep 20, 2026
12views this month
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Trust & integrity
| Signal | LLM.swift | airllm |
|---|---|---|
| Maintenance | Steady (62d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings 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
- LLM.swift
- LLM.swift enables local interaction with large language models for multiple Apple platforms.
- airllm
- Inference for AirLLM 70B model with single 4GB GPU
Stars
- LLM.swift
- 877
- airllm
- 35k
Forks
- LLM.swift
- 126
- airllm
- 3.6k
Open issues
- LLM.swift
- 10
- airllm
- 155
Language
- LLM.swift
- Swift
- airllm
- Jupyter Notebook
Adopt for
- LLM.swift
- LLM.swift is a cross-platform C++ library for Apple systems that simplifies local interaction with large language models.
- airllm
- AirLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI.
Persona
- LLM.swift
- -
- airllm
- -
Runtime
- LLM.swift
- -
- airllm
- -
License
- LLM.swift
- MIT license allows for free use and distribution, both commercially and in open source projects, with attribution preferred but not mandatory.
- airllm
- Apache-2.0
Last pushed
- LLM.swift
- Jul 19, 2026
- airllm
- Sep 18, 2026
Categories
- LLM.swift
- Inference & Serving
- airllm
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- LLM.swift
- Steady (60%)
- airllm
- Very active (96%)
Days since push
- LLM.swift
- 62d
- airllm
- 0d
Open issues (now)
- LLM.swift
- 10
- airllm
- 155
Stars delta
- LLM.swift
- +12 (30d)
- airllm
- +10k (30d)
Open issues delta
- LLM.swift
- +1 (30d)
- airllm
- +40 (30d)
OSV dependency advisories
- LLM.swift
- No lockfile (source not queried)
- airllm
- Published findings
Full report
- LLM.swift
- Trust report
- airllm
- Trust report
Choose LLM.swift if…
- LLM.swift is primarily Swift; airllm is Jupyter Notebook.
- License: LLM.swift is MIT, airllm is Apache-2.0.
- Pricing: Free to use under the MIT License. Premium support may vary..
- Tags unique to LLM.swift: gguf, ios, llm-inference, macos.
- Choose LLM.swift when you need to integrate large language model functionalities into apps targeting multiple Apple platforms, including macOS and mobile OSes.
When NOT to use LLM.swift
- Avoid LLM.swift if your application must run on non-Apple systems or if compatibility across various operating systems is prioritized over ease-of-use on Apple platforms.
- Do not use this library if you require advanced server-side functionalities, as it focuses specifically on local interactions within Apple’s ecosystem.
Choose airllm if…
- airllm is primarily Jupyter Notebook; LLM.swift is Swift.
- License: airllm is Apache-2.0, LLM.swift is MIT.
- Requirements: Min 4 GB RAM; Installation is straightforward via pip..
- Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai.
- Also covers LLM Frameworks.
- When you need to perform inference on a 70B parameter model with limited GPU resources, such as a single 4GB GPU.
When NOT to use airllm
- If your project requires inference on models larger than 70B parameters or if you have access to more powerful GPUs than a 4GB model.
- For projects that do not involve Chinese language models or generative AI tasks, as AirLLM is specifically optimized for these areas.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (eastriverlee/LLM.swift) · observed Sep 20, 2026
- GitHub forks (eastriverlee/LLM.swift) · observed Sep 20, 2026
- Last push (eastriverlee/LLM.swift) · observed Jul 19, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (lyogavin/airllm) · observed Sep 20, 2026
- GitHub forks (lyogavin/airllm) · observed Sep 20, 2026
- Last push (lyogavin/airllm) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: LLM.swift 877 · airllm 35k (synced Sep 20, 2026).
Common questions
- What is the difference between LLM.swift and airllm?
- LLM.swift: LLM.swift enables local interaction with large language models for multiple Apple platforms.. airllm: Inference for AirLLM 70B model with single 4GB GPU. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLM.swift over airllm?
- Choose LLM.swift over airllm when LLM.swift is primarily Swift; airllm is Jupyter Notebook; License: LLM.swift is MIT, airllm is Apache-2.0; Pricing: Free to use under the MIT License. Premium support may vary.; Tags unique to LLM.swift: gguf, ios, llm-inference, macos; Choose LLM.swift when you need to integrate large language model functionalities into apps targeting multiple Apple platforms, including macOS and mobile OSes.
- When should I choose airllm over LLM.swift?
- Choose airllm over LLM.swift when airllm is primarily Jupyter Notebook; LLM.swift is Swift; License: airllm is Apache-2.0, LLM.swift is MIT; Requirements: Min 4 GB RAM; Installation is straightforward via pip.; Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai; Also covers LLM Frameworks; When you need to perform inference on a 70B parameter model with limited GPU resources, such as a single 4GB GPU.
- When should I avoid LLM.swift?
- Avoid LLM.swift if your application must run on non-Apple systems or if compatibility across various operating systems is prioritized over ease-of-use on Apple platforms. Do not use this library if you require advanced server-side functionalities, as it focuses specifically on local interactions within Apple’s ecosystem.
- When should I avoid airllm?
- If your project requires inference on models larger than 70B parameters or if you have access to more powerful GPUs than a 4GB model. For projects that do not involve Chinese language models or generative AI tasks, as AirLLM is specifically optimized for these areas.
- Is LLM.swift or airllm more popular on GitHub?
- airllm has more GitHub stars (34,504 vs 877). Stars measure visibility, not whether either tool fits your constraints.
- Are LLM.swift and airllm open source?
- Yes - both are open-source projects on GitHub (LLM.swift: MIT, airllm: Apache-2.0).
- Where can I find alternatives to LLM.swift or airllm?
- GraphCanon lists graph-backed alternatives at LLM.swift alternatives and airllm alternatives (LLM.swift markdown twin, airllm 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, LLM.swift or airllm?
- LLM.swift: Steady. airllm: 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 LLM.swift and airllm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM.swift trust report; airllm trust report.