Comment by syntaxing
4 hours ago
Been using Qwen 3.6 35B and Gemma 4 26B on my M4 MBP, and while it’s no Opus, it does 95% of what I need which is already crazy since everything runs fully local.
4 hours ago
Been using Qwen 3.6 35B and Gemma 4 26B on my M4 MBP, and while it’s no Opus, it does 95% of what I need which is already crazy since everything runs fully local.
You've got me curious. Two questions if I may:
- What kind of tasks/work?
- How is either Qwen/Gemma wired up (e.g. which harness/how are they accessed)?
Or to phase another way; what does your workflow/software stack look like?
1. Qwen is mostly coding related through Opencode. I have been thinking about using pi agent and see if that works better for general use case. The usefulness of *claw has been limited for me. Gemma is through the chat interface with lmstudio. I use it for pretty much everything general purpose. Help me correct my grammar, read documents (lmstudio has a built in RAG tool), and vision capabilities (mentioned below, journal pictures to markdown).
2. Lmstudio on my MacBook mainly. You can turn on an OpenAI API compatible endpoint in the settings. Lmstudio also has a headless server called lms. Personally, I find it way better than Ollama since lmstudio uses llama cpp as the backend. With an OpenAI API compatible endpoint, you can use any tool/agent that supports openAI. Lmstudio/lms is Linux compatible too so you can run it on a strix halo desktop and the like.
Thanks I appreciate the info. I may try to spin up something like this and give it a whirl.
Do you use it with ollama? Or something else?
It’s good enough that I’ve been having codex automate itself out of a job by delegating more and more to it.
Very excited for the 122b version as the throughput is significantly better for that vs the dense 27b on my m4.
can you expand more on what you mean by 95%?
There are 2 aspects I am interested in:
1. accuracy - is it 95% accuracy of Opus in terms of output quality (4.5 or 4.6)?
2. capability-wise - 95% accuracy when calling your tools and perform agentic work compared to Opus - e.g. trip planning?
1. What do you mean by accuracy? Like the facts and information? If so, I use a Wikipedia/kiwx MCP server. Or do you mean tool call accuracy?
2. 3.6 is noticeably better than 3.5 for agentic uses (I have yet to use the dense model). The downside is that there’s so little personality, you’ll find more entertainment talking to a wall. Anything for creative use like writing or talking, I use Gemma 4. I also use Gemma 4 as a “chat” bot only, no agents. One amazing thing about the Gemma models is the vision capabilities. I was able to pipe in some handwritten notes and it converted into markdown flawlessly. But my handwriting is much better than the typical engineer’s chicken scratch.
by accuracy I meant how close is the output to your expectations, for example if you ask 8B model to write C compiler in C, it outputs theory of how to write compiler and writes pseudocode in Python. Which is off by 2 measures: (1) I haven't asked for theory (2) I haven't asked to write it in Python.
Or if you want to put it differently, if your prompt is super clear about the actions you want it to do, is it following it exactly as you said or going off the rails occasionally
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