Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for edge-AI developers who need a real agentic model for ESP32-S3 / Raspberry Pi 5 / sub-$200 phones, smart-home and robotics teams evaluating on-device tool-calling models, and mobile-app teams that need 28MB session RAM, 14MB binary, and Apple Vision Pro / Quest 3S performance.
Who should use it
Who should skip it
Skip cactus-compute/needle if the source repository or demo is inactive, unmaintained, or no longer matches the description shown here.
About this signal
cactus-compute/needle is tracked by RepoRadar as a model release in the On-Device Inference section. First seen 2026-08-11; the source record was last checked on 2026-08-11. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. cactus-compute/needle leads on workflow potential (9.9) and practical usefulness (9.0); its lowest signal is setup ease (6.4), so factor that in before investing setup time. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The cactus-compute/needle record combines a 8.8/10 composite score with separate popularity (5.4), risk (conditional), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.
Putting this into practice? Read Local AI vs. hosted APIs: how to choose for the checklist behind this score.
Risk explanation
It is a 14MB binary that runs full agentic sessions in 28MB of RAM; a misconfigured tool-calling prompt can exhaust the session RAM cap on smaller targets, so size the tool schema and watch the runtime memory budget on ESP32-S3 / sub-$200 phones.