How Hardware Hunter works

The full picture: what we watch, how we price things, what trips the scam filter, and what makes the cut for an alert.

Step 1What we watch

The scanner pulls from multiple sources every two hours. Each source requires different parsing logic — Reddit posts have a different format than eBay listings, and deal subreddits are different again from peer-to-peer swap subs.

r/homelabsales
Peer-to-peer, homelab gear, [H] format. Primary source for server/networking hardware.
r/hardwareswap
Broader peer-to-peer. CPU, GPU, RAM, storage. High volume.
r/buildapcsales
Retailer deal posts. GPU and CPU focus. Flair-based filtering.
r/DataHoarder
Storage-focused community. Hard drives, NAS gear, bulk deals.
eBay
Sold listings for benchmark data. Active listings for deal matching.
Slickdeals
Community-vetted retail deals. Catches new/refurb discounts alongside used.

Step 2How we know what's a good price

We maintain our own price benchmark table, built from historical scan data. For each category and subcategory, we track median price, p25 (low end of normal), and p75 (high end of normal) across a rolling window of recent listings.

This is what makes the scoring meaningful. "RTX 4070 Ti for $500" is only interesting if you know the current median is $575. Without that context, it's just a number.

Example: RTX 4070 Ti (current benchmarks)
p25 — low end of market $490
Median — typical price $575
p75 — high end of market $650
Why not just use eBay sold listings? We do use eBay data as one input, but our benchmark table also incorporates Reddit transaction prices, which skew lower than eBay for most categories. The homelab market genuinely is cheaper than eBay for enterprise gear — the benchmark should reflect that.

Step 3Scam signal detection

Before an LLM sees a listing, it passes through a heuristic filter that flags common patterns. A flagged listing isn't automatically rejected — the flags become inputs to the score.

New account age

Reddit accounts under 30 days old, or with very low karma, selling high-value items are a significant risk signal. Not a disqualifier on its own, but weighted heavily.

Vague or missing location

Legitimate sellers typically include a metro area. "USA" or no location at all is a flag, especially on peer-to-peer subs where location affects shipping expectations.

Price below floor

Price more than 30% below the p25 benchmark. Could be a real steal — but combined with other signals, it's a red flag. We check how many standard deviations below market the price sits.

Thin listing description

Very short description, no condition detail, no photos mentioned. Legitimate sellers typically describe condition and any defects. Missing this is a minor flag.

Trade history

For Reddit subs, confirmed trade count is a strong positive signal. Zero confirmed trades + new account + low price = high risk. Established sellers with 20+ trades get a meaningful score boost.

Step 4LLM evaluation

After the heuristics run, each listing is evaluated by DeepSeek Chat via LiteLLM. The model receives the listing details, your hunt criteria, the price benchmarks, and the scam signal flags. It outputs a score from 1–10 and a short verdict.

The prompt is specific: evaluate this exact listing against this exact hunt. Not a generic "is this a good deal?" — your criteria for brand, condition, capacity, and intended use are all in the context. This is what makes the score relevant to you rather than just to the market.

Cost per evaluation: approximately $0.004. The scanner evaluates hundreds of listings daily. The economics only work because we skip the LLM entirely for listings that obviously don't match your criteria before scoring.

Score Outcome What it means
8–10 Alert Act now. Good price, clean signals, matches your criteria. You get notified.
6–7 Watch Worth knowing about. Not urgent. You get notified but with lower priority framing.
1–5 Skip Doesn't meet the bar. Overpriced, suspicious signals, or doesn't match criteria. You don't hear about it.
What the LLM doesn't decide: Whether something fits your criteria is a hard check before scoring — wrong category, wrong socket, wrong capacity, above your price ceiling — these are filtered out before the LLM runs. The LLM evaluates quality within the matching set, not relevance. This keeps it focused and prevents score inflation.

Step 5Alerts

When a listing scores 6 or above, you get notified. Free tier: email alerts, scans every 6 hours. Pro tier: email + Telegram, scans every 2 hours.

The alert includes the listing title, price, source, score, and the LLM's verdict — the one-sentence reason it scored that way. You get enough context to decide in 10 seconds whether it's worth clicking through.

Alert volume is naturally low. The scanner evaluates hundreds of listings per day per active hunt. On a good day, you get 1–3 alerts. On a slow market day, zero. That's the point — if you're getting 20 alerts a day, something is wrong with the score threshold, not with the market.

Try it with a real hunt

Free tier includes 2 active hunts and email alerts. No credit card required.

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