Comparison
cactus vs airllm
Verdict
Pick cactus if cactus - Low-latency AI engine optimized for mobile and wearable devices; 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 · cactus alternatives · airllm alternatives
GraphCanon updated Sep 20, 2026
12views this month
Trust & integrity
| Signal | cactus | airllm |
|---|---|---|
| Maintenance | Active (11d since push) As of Sep 19, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 19, 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
- cactus
- Low-latency AI engine for mobile devices & wearables
- airllm
- Inference for AirLLM 70B model with single 4GB GPU
Stars
- cactus
- 6.0k
- airllm
- 35k
Forks
- cactus
- 505
- airllm
- 3.6k
Open issues
- cactus
- 103
- airllm
- 155
Language
- cactus
- C++
- airllm
- Jupyter Notebook
Adopt for
- cactus
- Cactus - Low-latency AI engine optimized for mobile and wearable devices.
- 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
- cactus
- -
- airllm
- -
Runtime
- cactus
- -
- airllm
- -
License
- cactus
- Other
- airllm
- Apache-2.0
Last pushed
- cactus
- Sep 8, 2026
- airllm
- Sep 18, 2026
Categories
- cactus
- Inference & Serving, Speech & Audio
- airllm
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- cactus
- Active (82%)
- airllm
- Very active (96%)
Days since push
- cactus
- 11d
- airllm
- 0d
Open issues (now)
- cactus
- 103
- airllm
- 155
Stars delta
- cactus
- +495 (30d)
- airllm
- +10k (30d)
Open issues delta
- cactus
- +21 (30d)
- airllm
- +40 (30d)
Owner type
- cactus
- Organization
- airllm
- User
OSV dependency advisories
- cactus
- No lockfile (source not queried)
- airllm
- Published findings
Full report
- cactus
- Trust report
- airllm
- Trust report
Choose cactus if…
- cactus is primarily C++; airllm is Jupyter Notebook.
- License: cactus is Other, airllm is Apache-2.0.
- Tags unique to cactus: ai, android, arm, edge.
- Also covers Speech & Audio.
- - When you need fast response times on mobile or wearable devices for tasks like speech recognition and general inference.
When NOT to use cactus
- - In situations that require high-complexity AI applications beyond general inference, such as detailed image segmentation or extensive natural language understanding tasks.
- - When working with desktop or server environments, as Cactus is specifically optimized for mobile and wearable hardware constraints.
Choose airllm if…
- airllm is primarily Jupyter Notebook; cactus is C++.
- License: airllm is Apache-2.0, cactus is Other.
- 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 (cactus-compute/cactus) · observed Sep 20, 2026
- GitHub forks (cactus-compute/cactus) · observed Sep 20, 2026
- Last push (cactus-compute/cactus) · observed Sep 8, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 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: cactus 6.0k · airllm 35k (synced Sep 20, 2026).
Common questions
- What is the difference between cactus and airllm?
- cactus: Low-latency AI engine for mobile devices & wearables. 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 cactus over airllm?
- Choose cactus over airllm when cactus is primarily C++; airllm is Jupyter Notebook; License: cactus is Other, airllm is Apache-2.0; Tags unique to cactus: ai, android, arm, edge; Also covers Speech & Audio; - When you need fast response times on mobile or wearable devices for tasks like speech recognition and general inference.
- When should I choose airllm over cactus?
- Choose airllm over cactus when airllm is primarily Jupyter Notebook; cactus is C++; License: airllm is Apache-2.0, cactus is Other; 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 cactus?
- - In situations that require high-complexity AI applications beyond general inference, such as detailed image segmentation or extensive natural language understanding tasks. - When working with desktop or server environments, as Cactus is specifically optimized for mobile and wearable hardware constraints.
- 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 cactus or airllm more popular on GitHub?
- airllm has more GitHub stars (34,504 vs 6,030). Stars measure visibility, not whether either tool fits your constraints.
- Are cactus and airllm open source?
- Yes - both are open-source projects on GitHub (cactus: Other, airllm: Apache-2.0).
- Where can I find alternatives to cactus or airllm?
- GraphCanon lists graph-backed alternatives at cactus alternatives and airllm alternatives (cactus 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, cactus or airllm?
- cactus: Active. 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 cactus and airllm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: cactus trust report; airllm trust report.