Interface matters: LLMs perform best when the UI does more than typed prompts. A thread argues linear interfaces bottleneck usability, slowing real-world use of powerful models [1].
On the UI front, Qwen offers a UI that mirrors OpenAI's feel—free access, an Android app, and a chat endpoint you can proxy into locally [2]. That openness lines up with tool calling via a proxy, letting local workflows connect to Qwen endpoints [2].
UI choices for general use show a spectrum. LM Studio is a great llama.cpp frontend for quick testing, while oobabooga’s text generation web UI offers more control and a different workflow [3].
On tooling, chatllm.cpp now supports LLaDA2.0-mini-preview, a 16BA1B Mixture-of-Experts model optimized for practical apps, with timings that put it in the same ballpark as Qwen3-1.7B in tests [4]. This setup is especially good at tool calling. The ecosystem also includes TabbyAPI and Exllamav3 for tool calling, though setup hurdles remain; some folks are using a tool-call proxy to fix gaps [5].
Bottom line: UI and tooling matter as much as models themselves. In 2025, watch how on-device UIs, tool calling, and multi-model frontends converge into practical LLM workflows.
References
LLMs Are Bottlenecked by Linear Interfaces
Argues LLMs are limited by linear interfaces; emphasizes interface design affects usability and performance perception; proposes alternative interfaces for efficiency.
View sourceQwen offers similar UI to openai - free, has android app
Discusses Qwen's free, OpenAI-like UI and image support, open source models, censorship debates, and local deployment via proxies.
View sourceWhat UI is best for doing all kind of stuff?
Discusses UI frontends, model ranges (24-30B), training, tools integration, and setup tips for local LLM usage on 3090.
View sourcechatllm.cpp supports LLaDA2.0-mini-preview
Discusses LLaDA2.0-mini-preview performance, compares with Qwen3-1.7B and Ling, includes timings, run without Python option, and quant suggestions.
View sourceTool Calling with TabbyAPI and Exllamav3
Users discuss struggles enabling tool calling with Exllamav3 via TabbyAPI, sharing configs, datasets, and forks; some tools succeed differently today.
View source