I spent $266 and four AI models to own my tablet. GLM-5.3 finished it in a day
- ID
- 17128
- Status
- summarized
- Published
- 23 Aug 2026, 10:23 PM
- Fetched
- 25 Aug 2026, 12:24 PM
- Provider
- Hacker News
- Category
- dev-community
- Original URL
- https://ericpardee.github.io/fire-hd-ownership/
- Source URL
- https://hnrss.org/best
Summary
- Score
- 7.5
- Created
- 25 Aug 2026, 12:25 PM
- Tags
- Audience
- developersvibe_codersai_agent_users
What happened
An author with 20 years in tech and an InfoSec background spent $266.15 across four AI models to root an Amazon Fire HD 10 (11th gen, 2021) that had no published root method because Amazon fused the bootrom shut. Claude spent five months on diagnosis before its safeguards cut him off; Kimi K3 (Moonshot AI, released July) found the exploit for $164.25, GLM-5.2 caught fatal bugs for $21.90, and GLM-5.3 finished the job in one day on an $80 subscription. The author notes the most sophisticated technique he used was prompting an LLM.
Why it matters
This is a concrete cost-and-capability comparison across frontier models for a real agentic security task: Claude hit guardrail limits after five months, while Kimi K3 reasoned through the ethics and produced a working exploit for $164. If you're choosing AI coding agents for hard reverse-engineering or security work, this suggests model guardrails and persistence vary enough to justify running multiple models in parallel rather than committing to one vendor.
Discussion angle
The guardrail divergence is the real story: Claude refused after months of work, while Kimi K3 talked itself into helping by reasoning about device ownership legality. What does that mean for picking models when your task sits near a safety boundary?