The questions below the divider were asked by real people on the Hacker News and r/raspberry_pi threads, named. The v0.4 questions above it are the ones the release video raises. Answers are checked against the repo and measured runs on the real car.
Q: How do I actually talk to the car? (v0.4) A: Say a wake phrase ("Hello car", "Hey car", "Hei auto") or tap Speak on the phone dashboard, then ask in the same breath. For 30 seconds after an answer you can keep talking with no new wake phrase. Everything before the wake phrase is discarded, so talking NEAR the car does not summon it.
Q: Does it really work with no internet? (v0.4) A: Yes - the last question in the release video is asked after switching the phone hotspot off on camera. Speech-to-text (whisper.cpp), the model, and the voice (piper) all run on the Pi. To be precise about the split: OBD readings and owner's-manual answers work fully offline - they never left the car. The Mercedes me fuel/tyre/charge tiles are the separate ONLINE enrichment; offline they show last-known values, labeled as such. Room transcript posts also resume when the connection returns.
Q: Will it answer its own voice, or the radio? (v0.4) A: Not anymore, and the release video is why we can say that: during filming the car heard the tail of its own answer and replied to itself. v0.4 ships the echo gate - the mic stays closed until the cabin audio has actually finished, and anything that transcribes as a copy of the car's last answer is dropped. Ambient speech without a wake phrase is ignored and never posted.
Q: The answers in the video stutter. Known? (v0.4) A: Known, root-caused after the shoot, fixed the same evening: the Bluetooth OBD dongle was polled every ~20 s on the same radio that carries the answer audio, and voice answers never set the radio-quiet window the daily brief already used (commit b6904bf closes exactly that). The journal-forensics write-up is in the commit message; the next filmed answer is the proof run.
Q: Can it see - dashcam, camera, "look at this light"? (v0.4) A: Not yet. The candidate is benched: Gemma 4 12B (multimodal, vision projector already on the SD card) runs at 1.5 tokens/s generation on the Pi - too slow to talk with, plausible as a slow background frame-reader. It stays a candidate until something is proven on the real car.
Q: What hardware do you need? (yjftsjthsd-h, HN) A: A Raspberry Pi 5, a ~15 € Bluetooth ELM327 OBD adapter (Vgate iCar Pro is the tested unit), and a power source in the car. No cables into the car beyond the OBD dongle, no soldering. The engine values (RPM, coolant, speed, hybrid battery, 12 V) are standard OBD-II.
Q: Which runtime, and what speed do you really get? (pranaysparihar, Reddit) A: llama.cpp, serving Qwen3.6-35B-A3B in Unsloth's UD-Q3_K_S dynamic quant (14.3 GB). Measured on the real Pi in the real car: 3.5 tokens/s generation, 25+ tokens/s prompt processing, 65 °C sustained. A full spoken, manual-grounded answer takes roughly 1.5-4 minutes (approximate measured range) depending on the question and how hot the cabin is - the dash strip shows live progress while it thinks. That is honest; it is a car that thinks before it speaks, not a chatbot race. (Faster brains are being benched in the open: Gemma 4 12B measured 1.5 tok/s - slower, rejected; Ornith-1.5-35B-A3B is on the bench tonight.)
Q: Why Qwen 35B-A3B and not Gemma 4 E4B? (dofm, HN) A: The A3B matters more than the 35B: it is a mixture-of-experts model with ~3B parameters active per token, so it fits the Pi's memory as a quant and still generates at usable speed. Dense models of comparable quality either do not fit or crawl. We publish the measured numbers rather than claiming it is fast.
Q: Is the model trained or fine-tuned for cars? (javier123454321, HN) A: No. It is a stock open-weight model. The car knowledge comes from grounding, not training: live OBD values are passed to it verbatim, and the owner's manual is chunked with page numbers so answers cite the page they came from.
Q: What is the LLM actually for, then? (hypfer, HN) A: It is the interface, not the sensor. The real data comes from OBD, Home Assistant, and the manual; the model turns a spoken question into the right lookup and the numbers into a sentence. When it has no data, the rules force it to say so instead of improvising.
Q: How does the Pi do TLS to the manufacturer API? (Reubachi, HN) A: It does not talk to the manufacturer at all. The Pi reads your Home Assistant over Tailscale, and HA holds the Mercedes integration and its credentials. There are no manufacturer credentials in the car. (see carwatch/cloudcar.py)
Q: How does it handle uncertainty about trim and year? (jiangriver66, HN) A: By saying so. The manual RAG cites pages, live values are quoted as read, and the system prompt requires it to state plainly what it does not know. The "Stated by the Berry" section shows what that sounds like in practice.
Q: Shouldn't the Pi collect data and a bigger machine at home think? (EightyNineMillion, Reddit) A: That works, and nothing in the architecture forbids it; the room protocol does not care where the brain lives. We run the brain in the car because the car should answer in a parking garage with no home dependency, and because the data staying in the car is the privacy story. If you prefer a home box, point the same services at it.
Q: Should you trust anything a Pi-sized LLM says about your car? (trouthat, Reddit; "the weights are the weights", AllRealityIsVirtua1) A: No, and the design assumes you should not. The model is never the source of truth: OBD numbers pass through verbatim, manual answers carry page citations, and anything unverified is labeled. The status table in the README marks every feature proven / in testing / planned, and "proven" means it worked on the real car.
Q: "A lot of this looks aspirational." (VTimofeenko, HN, quoting the README's own "unverified against the real car" line) A: Fair, and that line exists on purpose. The README keeps a status table with an honesty policy: nothing is marked proven until it ran against the real car. What is proven today: OBD live readings, the room agent, manual RAG with page citations, the phone dashboard, and on-Pi voice transcription. What is not is listed just as plainly.
Notes for review: the Reddit thread also contained "this reads like an ad" (lostrouteros). I suggest we answer that by keeping this FAQ exactly this dry.