head to head · open source
local-deep-research vs teslamate
local-deep-research has 9,499 GitHub stars, 903 forks, 889 open issues and last shipped yesterday. teslamate has 9,230 stars, 1,041 forks, 72 open issues and last shipped 2 days ago. local-deep-research leads on adoption by 3% (9,499 vs 9,230 stars). local-deep-research is written in Python under MIT; teslamate is written in Elixir under AGPL-3.0. local-deep-research has attracted 10% as many forks as stars, teslamate 11%. local-deep-research was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (home-automation), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| local-deep-research | teslamate | |
|---|---|---|
| GitHub stars | ★ 9.5K | ★ 9.2K |
| License | MIT | AGPL-3.0 |
| Written in | Python | Elixir |
| Last push | 2026-11-04 | 2026-11-03 |
| Forks | ⑂ 903 | ⑂ 1.0K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick local-deep-research if
- You weight community size — 9.5K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick teslamate if
- You want the teslamate feature set and don't need the biggest community
- You prefer the AGPL-3.0 license terms
- Your stack matches Elixir
- You evaluated both and teslamate fits your workflow better
About local-deep-research
Local Deep Research AI powered research assistant for deep, agentic research Performs deep, agentic research using multiple LLMs and search engines with proper citations 🧪 First open source project — fully local on a single RTX 3090 (Qwen3.6 27B) — to report 95% SimpleQA (n=500) and 77% xbench DeepSearch (n=100) on local hardware. See the r/LocalLLaMA announcement and the benchmark dataset. ▶️ Watch Review by The Art Of The Terminal 🚀 What is Local Deep Research? AI research assistant you control. Run locally for privacy, use any LLM and build your own searchable knowledge base. You own your data and see…
read the full local-deep-research overview →
About teslamate
TeslaMate A powerful, self hosted data logger for your Tesla. Written in Elixir Data is stored in a Postgres database Visualization and data analysis with Grafana Vehicle data is published to a local MQTT Broker ⚠️ Security Warning [!CAUTION] Use Official Versions Only To protect yourself from malicious forks, malware, and data theft, please ensure you only obtain TeslaMate from the official source: Official Repository: Official Documentation: We have received reports of deceptive websites and unofficial mobile apps (e.g. on the App Store) using the TeslaMate name to distribute modified or harmful versions. If…
read the full teslamate overview →
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Frequently asked questions
Is local-deep-research or teslamate more popular?
local-deep-research has 9,499 GitHub stars and teslamate has 9,230. local-deep-research has the larger community by that measure.
Are local-deep-research and teslamate free?
Both are open source. local-deep-research is licensed under MIT and teslamate under AGPL-3.0. Neither carries a licence fee.
What is the difference between local-deep-research and teslamate?
local-deep-research is written in Python and teslamate in Elixir. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, local-deep-research or teslamate?
Choose local-deep-research if you want the larger community (9,499 stars) or its MIT licence terms. Choose teslamate if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.