hardware-llm-optimizer-v2AI硬件LLM推荐工具 - 基于llmfit内核。自动检测CPU/GPU/RAM/VRAM → 智能推荐最适合的大模型 + 量化方案 + 速度估算。支持100+模型库，内置TUI界面和硬件模拟。
Install via ClawdBot CLI:
clawdbot install smseow001/hardware-llm-optimizer-v2Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses system directories or attempts privilege escalation
/proc/Calls external URL not in known-safe list
https://llmfit.axjns.dev/install.shAI Analysis
The skill's primary function is hardware analysis and model recommendation using a local tool (llmfit). The external URL is for installing this tool, which aligns with the skill's stated purpose. The `/proc/` access is typical for hardware detection and does not indicate privilege escalation beyond reading system information.
Audited Apr 18, 2026 · audit v1.0
Generated Jul 9, 2026
When a user asks what large language model their computer can run, this tool automatically detects hardware specs and recommends the best model with quantization and speed estimates. Ideal for retail tech support or DIY builders.
IT teams can simulate different GPU/RAM configurations using hardware simulation to plan LLM deployment across servers. Helps decide which models fit into existing infrastructure before purchase.
Developers working on edge devices with limited VRAM (e.g., 2GB-6GB) use the tool to find quantized models that fit and estimate inference speed. Useful for robotics, smart cameras, and IoT.
SaaS platforms offering AI features can integrate this tool to automatically select the best model for each customer based on their hardware, optimizing performance and cost per query.
Offer basic hardware detection and recommendations for free, charge for advanced features like batch hardware simulations, custom model lists, and API access for integration into other tools.
License the llmfit engine to hardware OEMs (e.g., PC manufacturers) or AI software vendors to embed in their products. Each license provides white-label integration and priority updates.
Offer paid consulting services to enterprises to create custom model recipes, performance benchmarks, and hardware configuration guides tailored to their specific use cases and workloads.
💬 Integration Tip
The llmfit CLI is already installed at /usr/local/bin/llmfit; use 'llmfit recommend --json' for programmatic access to structured results.
Scored Jul 9, 2026
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