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Show HN: I made a Raspberry with Qwen my local car AI

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Re: Show HN: I made a Raspberry with Qwen my local car AI

#21
post #3

Cool — but is that model really the right choice for the task? I guess it is only 3B active which helps a lot but is Gemma 4 E4B not more practical?

Qwen3.5-4B would be a good (better?) candidate. It uses a gated, deltanet hybrid, so your KV cache stays nearly flat as context grows, important for RAM-constrained environments like the Pi.

Re: Show HN: I made a Raspberry with Qwen my local car AI

#22
post #14

Fair warning, I have found local models and frontier models to be very bad at the specifics when it comes to cars. Small differences like month and year model can impact oil capacity, oil weight and things like that, the details that matter quite a bit. I found frontier models couldn't get things like what engine was in a 1994 Nissan Skyline, one of the more infamous and talked about cars on internet forums for decad…

This seems to be trained(? or referencing) on the specific cars' owner's manual.

[deleted]

Re: Show HN: I made a Raspberry with Qwen my local car AI

#23

I will shamelessly plug https://pitstop.app . I've been working on this for years and I work on/race cars regularly. I wouldn't fully trust LLMs with this :p BUT this project is still really freaking sweet.

Very cool! Working on a product for in-care use as well, complementary to this. Would love to talk shop!

Re: Show HN: I made a Raspberry with Qwen my local car AI

#25
post #14

Fair warning, I have found local models and frontier models to be very bad at the specifics when it comes to cars. Small differences like month and year model can impact oil capacity, oil weight and things like that, the details that matter quite a bit. I found frontier models couldn't get things like what engine was in a 1994 Nissan Skyline, one of the more infamous and talked about cars on internet forums for decad…

This seems to be trained(? or referencing) on the specific cars' owner's manual.

Yeah referencing is the way to go, as even finetuning probably captures style more than concrete facts. I know with large context windows we don't really RAG anymore, but for owner's manual lookup with a smaller model it seems ideal.

Something every LLM user ends up learning is that they're far better used as search and summarization tools than as knowledge databases in themselves.

Re: Show HN: I made a Raspberry with Qwen my local car AI

#26
post #14

Fair warning, I have found local models and frontier models to be very bad at the specifics when it comes to cars. Small differences like month and year model can impact oil capacity, oil weight and things like that, the details that matter quite a bit. I found frontier models couldn't get things like what engine was in a 1994 Nissan Skyline, one of the more infamous and talked about cars on internet forums for decad…

Just a few hours ago I gave ChatGPT my window sticker and the installation manual for a new suspension setup. I asked for new hardware that would typically be replaced during this install, like torque-to-yield bolts and fasteners. I also asked for new oil filters. I got a comprehensive grid of the exact part numbers needed in a nice dense table. sol 5.6 high is my daily driver.

Re: Show HN: I made a Raspberry with Qwen my local car AI

#27
post #14

Fair warning, I have found local models and frontier models to be very bad at the specifics when it comes to cars. Small differences like month and year model can impact oil capacity, oil weight and things like that, the details that matter quite a bit. I found frontier models couldn't get things like what engine was in a 1994 Nissan Skyline, one of the more infamous and talked about cars on internet forums for decad…

It's nothing that tool calling/feeding it the correct information can't solve

Re: Show HN: I made a Raspberry with Qwen my local car AI

#28
I’d be most interested in how it handles uncertainty when the answer depends on trim/year or service history. For a car assistant, a useful default might be “I found the relevant manual section, but this is ambiguous” rather than a direct fix. Do you surface the source page or confidence anywhere?
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