151–160 of 317 posts
I can't bring myself to use any model that trains or sends telemetry back to my country's primary competitor/adversary. I don't care how much money is saved.
Yeah, I prefer my data to be used and trained by the very trustworthy and benevolent tech oligarchs in my home country.
Earlier quoted context omitted.
I think you are being ridiculous. Tampering with an LLMs pretraining is a difficult undertaking. There is plenty of evidence that training a model to walk the party line leaves it less capable than if it weren't. It's not very subtle manipulation either; ask qwen of Taiwan is a part of China in German and in English and only the English answer will be party-approved.
Compared to what we have proof the US government have engaged in before? Do people not remember PRISM anymore? It was virtually impossible to think of the scope before it was leaked, and you'd be marked as a conspiracy theorist for believing that happened, before it was made concretely true. I think it's borderline naive to assume various agencies haven't infiltrated OpenAI, Anthropic and others, essentially the enti…
I was getting dangerously close to my weekly Claude Code limit last night so I had Claude set up Qwen3.6 with llama.cpp and OpenCode. Honestly it's a great (free!) alternative to Claude Code--certainly more than good enough for a lot of smaller less complex tasks. I'm excited to try this new version. The fact that open-source models are so close to the frontier is very impressive.
Which exact model are you using? And with which parameters and quant? And on what hardware? Are you using any specific MCPs or other tools to optimize performance like context-mode or dynamic context pruning? I’ve used local models a reasonable amount before but I’m just starting out with opencode. Haven’t had great results yet but really want this to work for simpler tasks. My opencode newly installed is also having…
/Users/gcr/llama.cpp/build/bin/llama-server
-hf unsloth/Qwen3.6-35B-A3B-GGUF:Q4_K_M
--no-mmproj-offload
--fit on
-c 65536 # edit to taste
--reasoning on --chat-template-kwargs '{"preserve_thinking": true}'
--sleep-idle-seconds 90 # very aggressive: purge model from vram after this long
-ctk q8_0 -ctv q8_0 # Optional. Lower memory use, but lower speed. Omit if you can.
For agent harnesses, opencode is okay, as is pi or even Zed's built in agent panel. Claude code "works" with ANTHROPIC_BASE_URL=http://localhost:8080/v1, but is very chatty (the default system prompt burns 20k tokens). Crush (from the charm-bracelet folks) is particularly nice when starting out. I've personally converged on pi-agent under an otherwise-mostly-default setup. You can ask qwen to customize pi or write you an extension which helps a little.
You'll need to add `http://localhost:8080/v1` as an OpenAI-compatible model provider in your coding harness with any API key (doesn't matter) and any model identifier (doesn't matter with llama-cpp).
Note that pi doesn't have permissions. Everything is permitted. The hundred hungry ghosts you've trapped in a jar WILL find a way to delete your home folder someday. That's what Man gets for summoning demons without casting a circle of protection first. Flying too close to the sun etc etc etc
Take backups and then go have fun. Hope this helps.
Earlier quoted context omitted.
The Ryzen AI Max 395 128gb is super cool, but not fast for inference. Order of magnitude slower than dedicated GPU but at half the cost. You can run larger models on it but it's slow. Great for local async work. Not great for daily chat or code agent driver.
The latest NPUs are pretty fast, I think what is missing is more optimised software support.
I was getting dangerously close to my weekly Claude Code limit last night so I had Claude set up Qwen3.6 with llama.cpp and OpenCode. Honestly it's a great (free!) alternative to Claude Code--certainly more than good enough for a lot of smaller less complex tasks. I'm excited to try this new version. The fact that open-source models are so close to the frontier is very impressive.
Earlier quoted context omitted.
It's highly improbable that the US government has a secret team inside Anthropic and OpenAI manipulating their training regimen. For better or worse, these companies are filled with ideologues and something that invasive would trigger an army of whistleblowers (despite legal consequences).
It's highly improbable that the US government has a secret team inside Anthropic and OpenAI manipulating their training regimen. Two thoughts. One: it would be relatively technically trivial for $GOVERNMENT_AGENCY to just monitor all the prompts + context we send over the wire to OpenAI/Anthropic/etc. That's a goldmine of sensitive personal and corporate data, no secret team needed (although, the LLM providers obviou…
Where can a user reasonably host this in an affordable way to access the local LLM revolution?
I was getting dangerously close to my weekly Claude Code limit last night so I had Claude set up Qwen3.6 with llama.cpp and OpenCode. Honestly it's a great (free!) alternative to Claude Code--certainly more than good enough for a lot of smaller less complex tasks. I'm excited to try this new version. The fact that open-source models are so close to the frontier is very impressive.
Out of interest, what machine and model are you running it on? I tried the qwen3.6-27b Q6_k GUFF in llama.cpp and LM Studio on my M2 MacBook Pro 32GB machine last week, and I barely get a token a second with either. What sort of speed should I be expecting? I tried some of the Llama 3 34b (nous-capybara?) models two years ago with llama.cpp, and I seem to remember getting a few tokens a second then, so not sure if I'…
I really like what Qwen are doing, and a lot of these Chinese labs, but until I can ask their models what happened during the student protests in 1989 or why human rights groups are upset about the Uighurs and the model gives me a straight answer I'm just not able to trust these models with anything of substance.
This is silly. Would you perform the same test against Western models in asking them whether Israel is a genocidal apartheid state? It'll give you the same roundabout explanations and "some say no some say yes" responses that you'll get from asking Qwen about Uighurs or the protests of 1989.
> Oops! There was an issue connecting to Qwen3.6-Plus.
> Content Security Warning: The input text data may contain inappropriate content.
hey ChatGPT, how many civilians were killed in Gaza in the war since 2023?
> [one page of estimates from local and international sources with links]
I was getting dangerously close to my weekly Claude Code limit last night so I had Claude set up Qwen3.6 with llama.cpp and OpenCode. Honestly it's a great (free!) alternative to Claude Code--certainly more than good enough for a lot of smaller less complex tasks. I'm excited to try this new version. The fact that open-source models are so close to the frontier is very impressive.
Out of interest, what machine and model are you running it on? I tried the qwen3.6-27b Q6_k GUFF in llama.cpp and LM Studio on my M2 MacBook Pro 32GB machine last week, and I barely get a token a second with either. What sort of speed should I be expecting? I tried some of the Llama 3 34b (nous-capybara?) models two years ago with llama.cpp, and I seem to remember getting a few tokens a second then, so not sure if I'…
- A 27B "dense" model
- A 35B "Mixture of Experts" model, which activates only 3B parameters for each token.
For your hardware, I strongly recommend `unsloth/Qwen3.6-35B-A3B-GGUF:Q4_K_M`. I have an M1 Max with 32GB VRAM from 2021 that can read at ~300-500 tokens/sec and write at ~30 tokens/sec with llama-cpp's default settings, which is plenty fast. The 27B model can read ~70tok/sec and write ~5tok/sec.
The 35B MoE model technically takes slightly more memory but is much faster because it's doing 1/9th the work. It's not quite as "smart", but it's comparable.