ByteBot is the first Computer Use Agent I’ve seen that actually works with local models. That’s not hype—it's a signal that on-device LLMs are finally hitting real-world usability [1].
Reliability on local models ByteBot’s success shows local models can run tasks that feel usable, even if the setup isn’t flawless. It’s a pointer to a broader shift: local-first work is becoming practical when the tooling and sandboxing are lean enough [1].
Tool usage & coding reality AMD tested 20+ local models for coding and found only 2 consistently usable: Qwen3-Coder 30B (4-bit, 8-bit) and GLM-4.5-Air for machines with 128GB+ RAM. For 32GB RAM, 4-bit Qwen3-Coder 30B is essentially the only viable option; with 64GB you can run 8-bit, and 128GB+ unlocks GLM-4.5-Air [2]. Other models like deepseek/deepseek-r1-0528-qwen3-8b and similar Llama variants were unreliable for tool-calling [2]. AMD used Cline and LM Studio for validation, tying tool-calling demands to real-world viability [2]. Magistral Small gets a nod as an honorable mention [2].
Hardware realities & quantization The reality is RAM matters a lot, and quantization (4-bit vs 8-bit) drives what fits on consumer-to-midrange boxes. Projects like llm-compressor (maintained with the same group as vllm) hint at faster, more scalable paths for on-device inference [3]. Expect mentions of high-quality quantization like GLM 4.6 as tooling improves [3].
Legacy hardware & eGPU world High-end, older GPUs still matter. A setup built around Nvidia Tesla V100 (64G) demonstrates how enterprise-class memory and bandwidth can extend local testing, with discussions of PCIe adapters and even a compact “RTX Pro Server” vibe for experimenting with big models on the cheap [4].
Closing thought: the local-LMM dream is code-heavy and hardware-hungry today, but the right quantization and vetted models are steadily narrowing the gap.
Referenced posts: [1], [2], [3], [4]
References
ByteBot - Why no hype train for these guys? This is the first Computer Use Agent I’ve seen actually work with local models!
User praises ByteBot as best local CUA; compares with Ollama, LM Studio, Open Router; notes models and forks for context
View sourceAMD tested 20+ local models for coding & only 2 actually work (testing linked)
AMD tested 20+ local models for coding; few worked reliably, e.g., Qwen3-Coder 30B, GLM-4.5-Air with RAM; many failed tool-calling overall.
View sourceHow can I use this beast to benefit the community? Quantize larger models? It’s a 9985wx, 768 ddr5, 384 gb vram.
Discusses quantizing large models; comparing AWQ vs GPTQ/NVFP4; seeks community-useful apps, benchmarks, and sharing hardware tips and experiences online forums.
View sourceThe Most Esoteric eGPU: Dual NVIDIA Tesla V100 (64G) for AI & LLM
Summaries the use of V100 SXM2 GPUs with NVLink for running LLMs; discusses adapters, benchmarks, costs, and opinions.
View source