alt Hacker NewsThis is basically my experience as well. I have a moderately recent but high spec desktop (Radeon 6900 XT with 16 GB VRAM, Ryzen 9 7900X 12-core, 64 GB system RAM), and I tried out some recommended models with ollama a month or two ago. Anything not geared specifically towards coding seemed to struggled with actually making tool calls instead of just stating the actions they would take without making them (and trying to get help from them to explain what I needed to configure to change that behavior was useless; qwen refused to believe that it was running in ollama and insisted that it was running from the Alibaba cloud without access to my local system), and the models intended for coding were barely thinking faster than I could type (if they had any ability to show thinking at all).
The best "free" experience I've found is using OpenCode with Big Pickle. It's not especially smart, so it often won't produce the correct result the first time, but the free tier is generous enough that I don't think I've hit the limit more than twice over around a month with frequent multi-hour sessions. If running locally is truly the goal, it's not going to fit the bill, but if the goal is just "get the best experience without having to pay for a sub or tokens", it's the least bad option I've found so far.
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Try llama.cpp it seems to be a lot more performant and a lot more hackable. Also I'm surprised how substantial the impact of some of the inference configs (beyond just temp) can have, though this is much more model specific.
> The best "free" experience I've found is using OpenCode with Big Pickle.
I have absolutely zero interest in free. I honestly don't think I'm even remotely in the same demographic as people using free tiers / models.
I want to pay. I don't want my data used for training. I want it to be open. I want it to be consistently up (more than Claude!). I want it to be fast. I don't want it to be subsidized as that's just an excuse for shitty quality. Deepseek flash knocks it out of the park on all of these except you're data is used in training. I'm fine with it being hosted since there's no way I'm using it 24/7, but data MUST be private.
Basically I want Hetzner and OVH to run open model clouds. I'm convinced this is going to happen eventually when everyone realizes this is a commodity.
I found that, with the heavily quantized Qwen3 models I can cram onto my 3060 Ti, telling the model to use its tools in the system prompt made it a lot more likely to actually do it. YMMV of course, but give it a shot.
For what it is worth, I’m on a similar machine. (9070XT,5900X) and found a lot of performance improvement over ollama by compiling llama.cpp and running with —no-mmap and —perf. The context is still quite small though. With online models I use contexts of at least 200k which is useful for longer running/more complicated commands.
Locally I haven’t gone much further than 8k. That is sufficient for small changes on small code bases. And you need condensed tool output.
I haven’t tried any tool that compresses the tokens yet.