Show HN: Distilling DeepSeek into GPT-OSS doesn't transfer censorship. Try it
What changed
While this latter belief has begun to attract attention in recent times, the experiments that do exist are largely confined to small scale toy scenarios and artificially steered teachers. We formalized and released our instrument LineageEval, utilizing matched pairs, four judges from four labs, and self-hosted teacher weights. The released 20B passed our pre-registered retention gates.
Why it matters
A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.
How it compares
Related prior coverage to compare against:
- gpt-oss-120b & gpt-oss-20b Model Card
- Nvidia, Microsoft, Meta warn against overregulating open-weight models
- Show HN: Echo – Fable-level results at 1/3 the cost using open-weight models
Sources
- Show HN: Distilling DeepSeek into GPT-OSS doesn't transfer censorship. Try it (hn-frontpage)primary