How to Build Real-World AI Agents with Qwen3.6-Plus
Most LLMs are great at vibes and terrible at work. Qwen3.6-Plus is Alibaba’s attempt to fix that with an agent-first model that actually… Continue reading on Medium »
Could not retrieve the full article text.
Read on Medium AI →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
modelagent
Gemma 4 26B A4B Single Page ASCII Chatbot Design
Built a single chatbot HTML page using Gemma 4 26B A4B running locally sharded between my 7900 XT and 3060 Ti with 32K context window at 50-65 t/s. Connects to LM Studio's API with full streaming, Markdown rendering, model selector, 6 parameter sliders, message editing with history branching, regenerate, abort, and system prompt support. Claude helped fix two DOM bugs that Gemma couldn't. Everything else was Gemma 4. GitHub: https://github.com/Shoggoth43/Gemma-4-26B-A4B-Generations submitted by /u/Reaper_9382 [link] [comments]
Best LLM for Mac Mini M4 Pro (64GB RAM) – Focus on Agents, RAG, and Automation?
Hi everyone! I just got my hands on a Mac Mini M4 Pro with 64GB . My goal is to replace ChatGPT on my phone and desktop with a local setup. I’m specifically looking for models that excel at: Web Search RAG: High context window and accuracy for retrieving info. AI Agents: Good instruction following for multi-step tasks. Automation: Reliable tool-calling and JSON output for process automation. Mobile Access: I plan to use it as a backend for my phone (via Tailscale/OpenWebUI). What would be the sweet spot model for this hardware that feels snappy but remains smart enough for complex agents? Also, which backend would you recommend for the best performance on M4 Pro? (Ollama, LM Studio, or maybe vLLM/MLX?) Thanks! submitted by /u/farmatex [link] [comments]
Ask HN: Will AI agents replace data scientists or make them better?
There's been a lot of chatter about AI agents replacing knowledge workers and I've been thinking about where data science specifically falls - the judgment part of the job feels different from the repetitive tasks. Curious what others are seeing in practice. Comments URL: https://news.ycombinator.com/item?id=47645141 Points: 2 # Comments: 0
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Models
Gemma 4 26B A4B Single Page ASCII Chatbot Design
Built a single chatbot HTML page using Gemma 4 26B A4B running locally sharded between my 7900 XT and 3060 Ti with 32K context window at 50-65 t/s. Connects to LM Studio's API with full streaming, Markdown rendering, model selector, 6 parameter sliders, message editing with history branching, regenerate, abort, and system prompt support. Claude helped fix two DOM bugs that Gemma couldn't. Everything else was Gemma 4. GitHub: https://github.com/Shoggoth43/Gemma-4-26B-A4B-Generations submitted by /u/Reaper_9382 [link] [comments]
Best LLM for Mac Mini M4 Pro (64GB RAM) – Focus on Agents, RAG, and Automation?
Hi everyone! I just got my hands on a Mac Mini M4 Pro with 64GB . My goal is to replace ChatGPT on my phone and desktop with a local setup. I’m specifically looking for models that excel at: Web Search RAG: High context window and accuracy for retrieving info. AI Agents: Good instruction following for multi-step tasks. Automation: Reliable tool-calling and JSON output for process automation. Mobile Access: I plan to use it as a backend for my phone (via Tailscale/OpenWebUI). What would be the sweet spot model for this hardware that feels snappy but remains smart enough for complex agents? Also, which backend would you recommend for the best performance on M4 Pro? (Ollama, LM Studio, or maybe vLLM/MLX?) Thanks! submitted by /u/farmatex [link] [comments]
Local Claude Code with Qwen3.5 27B
after long research, finding best alternative for Using a local LLM in OpenCode with llama.cpp to use totally local environment for coding tasks I found this article How to connect Claude Code CLI to a local llama.cpp server how to disable telemetry and make claude code totally offline. model used - Qwen3.5 27B Quant used - unsloth/UD-Q4_K_XL inference engine - llama.cpp Operating Systems - Arch Linux Hardware - Strix Halo I have separated my setups into sessions to run iterative cycle how I managed to improve CC (claude code) and llama.cpp model parameters. First Session as guide stated, I used option 1 to disable telemetry ~/.bashrc config; export ANTHROPIC_BASE_URL="http://127.0.0.1:8001" export ANTHROPIC_API_KEY="not-set" export ANTHROPIC_AUTH_TOKEN="not-set" export CLAUDE_CODE_DISABLE
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!