141–150 of 223 posts
On the topic of local models, is there a good equivalent to something like Claude's chat interface? I've recently started transitioning to open models after getting fed up with Claude's usage limits (I'm not in a position to drop $200/month), and for coding tasks Kimi 2.6 has been about the same as Sonnet in my experience. The only thing I've found myself missing is a nice interface to ask it questions and have it he…
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It's more about curating the things you're publishing. Why would I bother reading what you couldn't bother to read?
They could easily have read it, and thought , that communicates the information that it needs to. No point creating busywork for yourself just shuffling words around when the information is there, no? I guess it depends on what you want out of the article. Substance, or style?
I'd they aren't self-aware enough or smart enough to determine that what they wrote is indistinguishable from text generation, how probable is it that they have something of value to add to any thought?
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Qwen 3.6 burns it to the ground. it was not even a challenge. Gemma4 seriously fails at toolcalls and agentic works. It got all messed up after 2-3 turns of Vibecoding.
Counter-point: I built an agent that can only interface with Kakoune, a much less common and more challenging situation for an LLM to find itself in, and Gemma4-A4B 8bit quantized does remarkably better in actually figuring out how to get text in buffers than Qwen3.6-35B-A3B in a similar class as Gemma4 A4B. Now, is this the usual use case? No, it's a benchmark I created specifically in order to put LLMs in situation…
On the topic of local models, is there a good equivalent to something like Claude's chat interface? I've recently started transitioning to open models after getting fed up with Claude's usage limits (I'm not in a position to drop $200/month), and for coding tasks Kimi 2.6 has been about the same as Sonnet in my experience. The only thing I've found myself missing is a nice interface to ask it questions and have it he…
You can try Open WebUI. Its genuinely useful when it comes to running open models locally with a clean interface
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Qwen 3.6 burns it to the ground. it was not even a challenge. Gemma4 seriously fails at toolcalls and agentic works. It got all messed up after 2-3 turns of Vibecoding.
How do you run it? vllm? llama.cpp? Can you share some parameters you enable tool calling and agentic usage? Or, higher level, some philosophies on what approaches you are using for tuning to get better tool calling and/or agentic usage? I'm having surprisingly good success with unsloth/Qwen3.6-27B-GGUF:Q4_K_M (love unsloth guys) on my RTX3090/24GB using opencode as the orchestrator. It concocts some misleading paths…
My config is similar to: https://github.com/noonghunna/club-3090/blob/master/docs/eng...
I need to try out some of the other set ups mentioned in this repo for increased TPS.
I test drove it yesterday. It's pretty impressive at 8b. Runs on commodity hardware quickly. Qwen3.6 35b a3b is still my local champion but I may use this for auto complete and small tasks. Granite has recent training data which is nice. If the other small models got fine tuned on recent data I don't know if I would use this at all, but that alone makes it pretty decent. The 4b they released was not good for my needs…
I second this! Using the Unsloth Q6 (I forgot the exact name). Currently using it with forgecode (with zsh), on my Strix Halo, and it's suprisingly really good. I would say slightly Similar to Haiku 4.5, plus additional privacy, minus speed. It's surprisingly really fast for the hardware, given the speculative decoding, still PP is on the slow side.
> Full stop. Why people don't edit out obvious sloppification and expect to still have readers left
Third line in to the article: "But there’s one result in the benchmarks I keep coming back to." I hear this sort of thing all the time now on YouTube from media/news personalities: “And that’s the part nobody seems to be talking about.” "And here's what keeps me up at night." “This is where the story gets complicated.” “Here’s the piece that doesn’t quite fit.” “And this is where the usual explanation starts to break…
It's also exactly the Mr beast playbook, and got him to the largest channel on YouTube.
Any system attempting to capture human attention will use these techniques, nothing LLM-specific here at all.
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Apache 2.0 License. Did you not click the link to the project? They even list it in the article. > Apache 2.0 across the board, so commercial use is clean. Did you just stop when you saw open source and come post this here because you couldn't be bothered to... look at the project and see it's cleanly and clearly listed. Edit: Like. I get it. It's fine to question open source. But this isn't hidden. It's repeated and…
If I give you an amd64 elf binary under Apache2 license, is it open source?
If you check HF you will see its Apache2 and the datasets were also permissive.
It's one of the few models on the market where the creator indemnifies it against copyright claims.