[GitHub Trending] cactus-compute/needle

7.3 relevance

A 14MB foundation model for tiny devices is highly novel and relevant to AI/ML and edge computing.

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Why It Matters

For a Solutions Architect focused on AI/ML agent orchestration, Needle 2 offers a production-ready, ultra-lightweight model that can run tool-calling agents on edge devices or air-gapped infrastructure without external dependencies, directly addressing cost and latency constraints in multi-agent systems.

Key Takeaways

Evaluate Needle 2 for embedding tool-calling agents in resource-constrained environments, leveraging its 14MB binary and confidence-gated retrieval to reduce infrastructure overhead.

14MB foundation model for tiny devices; phones, wearables, smart home, and robots. - cactus-compute/needle

Summary

Needle 2 is a 45M-parameter open model for tool calling and structured extraction, compressed into a single 14MB binary that runs in ~28MB RAM. Built on a Simple Attention Network with Hadamard MLP and CQ2-bit quantization, it outperforms models 5-70x larger on benchmarks. The Python package provides inference, LoRA fine-tuning, and a confidence-gated, grammar-constrained tool retrieval system with a 256-token sliding window.

Author

cactus-compute