Comparison
Wax vs mem0
Verdict
Pick Wax if wax, a Swift-based memory layer for AI agents optimized on Apple Silicon via Metal, provides sub-millisecond RAG processing and operates entirely on-device without the need for external servers or APIs; pick mem0 if mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Markdown twin · Wax alternatives · mem0 alternatives
GraphCanon updated Oct 4, 2026
5views this month
Trust & integrity
| Signal | Wax | mem0 |
|---|---|---|
| Maintenance | Very active (1d 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 · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Oct 4, 2026 · osv@v1 | No lockfile (source not queried) 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
- Wax
- Single-file memory layer for AI agents with sub-millisecond RAG on Apple Silicon using Metal optimization
- mem0
- Drop-in memory infrastructure for AI agents and apps
Stars
- Wax
- 799
- mem0
- 66k
Forks
- Wax
- 54
- mem0
- 7.7k
Open issues
- Wax
- 0
- mem0
- 754
Language
- Wax
- Swift
- mem0
- Python
Adopt for
- Wax
- Wax, a Swift-based memory layer for AI agents optimized on Apple Silicon via Metal, provides sub-millisecond RAG processing and operates entirely on-device without the need for external servers or APIs.
- mem0
- mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Persona
- Wax
- -
- mem0
- -
Runtime
- Wax
- -
- mem0
- -
License
- Wax
- Apache-2.0
- mem0
- mem0 is distributed under the Apache-2.0 license, allowing for broad usage and modification with attribution.
Last pushed
- Wax
- Sep 18, 2026
- mem0
- Sep 18, 2026
Categories
- Wax
- AI Agents, Vector Databases
- mem0
- AI Agents, Data & Retrieval
Trust and health
Days since push
- Wax
- 1d
- mem0
- 0d
Open issues (now)
- Wax
- 0
- mem0
- 754
Stars delta
- Wax
- +26 (30d)
- mem0
- +2.8k (30d)
Open issues delta
- Wax
- -1 (30d)
- mem0
- +63 (30d)
Owner type
- Wax
- User
- mem0
- Organization
Full report
- Wax
- Trust report
- mem0
- Trust report
Choose Wax if…
- Wax is primarily Swift; mem0 is Python.
- Tags unique to Wax: cli, coreml, machine-learning, metal.
- Also covers Vector Databases.
- When developing AI applications that require extremely fast data retrieval with minimal latency on Apple devices.
When NOT to use Wax
- If your application targets non-Apple hardware, as Wax's performance optimization via Metal is specific to Apple Silicon.
- In scenarios where integration of Wax with existing complex backend services is necessary, since it does not rely on external APIs or servers for its operation.
Choose mem0 if…
- mem0 is primarily Python; Wax is Swift.
- Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost..
- Requirements: Min 2 GB RAM; Python environment is required for installation and use..
- Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory.
- Also covers Data & Retrieval.
- When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
When NOT to use mem0
- If your project is not in Python, as mem0 is specifically designed for Python environments.
- When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers.
- If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (christopherkarani/Wax) · observed Sep 20, 2026
- GitHub forks (christopherkarani/Wax) · observed Sep 20, 2026
- Last push (christopherkarani/Wax) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
- GitHub stars (mem0ai/mem0) · observed Sep 20, 2026
- GitHub forks (mem0ai/mem0) · observed Sep 20, 2026
- Last push (mem0ai/mem0) · 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: Wax 799 · mem0 66k (synced Sep 20, 2026).
Common questions
- What is the difference between Wax and mem0?
- Wax: Single-file memory layer for AI agents with sub-millisecond RAG on Apple Silicon using Metal optimization. mem0: Drop-in memory infrastructure for AI agents and apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose Wax over mem0?
- Choose Wax over mem0 when Wax is primarily Swift; mem0 is Python; Tags unique to Wax: cli, coreml, machine-learning, metal; Also covers Vector Databases; When developing AI applications that require extremely fast data retrieval with minimal latency on Apple devices.
- When should I choose mem0 over Wax?
- Choose mem0 over Wax when mem0 is primarily Python; Wax is Swift; Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost.; Requirements: Min 2 GB RAM; Python environment is required for installation and use.; Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory; Also covers Data & Retrieval; When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
- When should I avoid Wax?
- If your application targets non-Apple hardware, as Wax's performance optimization via Metal is specific to Apple Silicon. In scenarios where integration of Wax with existing complex backend services is necessary, since it does not rely on external APIs or servers for its operation.
- When should I avoid mem0?
- If your project is not in Python, as mem0 is specifically designed for Python environments. When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers. If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
- Is Wax or mem0 more popular on GitHub?
- mem0 has more GitHub stars (65,557 vs 799). Stars measure visibility, not whether either tool fits your constraints.
- Are Wax and mem0 open source?
- Yes - both are open-source projects on GitHub (Wax: Apache-2.0, mem0: Apache-2.0).
- Where can I find alternatives to Wax or mem0?
- GraphCanon lists graph-backed alternatives at Wax alternatives and mem0 alternatives (Wax markdown twin, mem0 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, Wax or mem0?
- Wax: Very active. mem0: 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 Wax and mem0?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Wax trust report; mem0 trust report.