We burned 11.7B tokens to find the best cyber AI model
piotrgrabowski
13 points
6 comments
August 21, 2026
Related Discussions
Found 5 related stories in 66.9ms across 6,054 title embeddings via pgvector HNSW
- AI models ran real businesses: They sent $12,431 in fake invoices, lost $3,200 Areibman · 98 pts · September 07, 2026 · 54% similar
- Choosing an AI model: one prompt, 11 models, different results toddmorey · 192 pts · August 13, 2026 · 53% similar
- I burned all my tokens researching how to save tokens bkotrys · 116 pts · July 19, 2026 · 53% similar
- Unlimited AI tokens aren't unlimited after all as US Army burns through supply Bender · 24 pts · July 22, 2026 · 52% similar
- What I Learned About AI Trust from Reconciling over 100B Transactions Cellz · 25 pts · August 31, 2026 · 52% similar
Discussion Highlights (4 comments)
LoganDark
Of course, the model trained most recently does the best job. Do we know what DeepSeek V4 Pro 0813's knowledge cutoff is? For all we know, it's simply working in parallel with how the vulnerabilities were first discovered, even if the solutions themselves weren't trained in. Surprised to see Grok 4.6 performing so well. Shame I can't use it privately -- I would never risk getting my Twitter account banned for that
exceptione
I don't see Fable, but I guess Fable would refuse to work anyway on cyber problems(?) But why would Opus 5 work then?
k4roshi
How was this so urgent that it required sleepless nights for the team?!
joker99
Since the “magic“ is in the harness: can anyone recommend a good OSS cyber harness? I’ve been experimenting a bunch at $work and for large heterogeneous code bases, just using codex or claude seems to work better than experimenting with tools like code graph/graphql to save on tokens