The Librarian is now ~3x faster and 43% cheaper, with the same quality.
It now runs on GPT-5.5 (no reasoning) with websocket mode and an updated system prompt that encourages more parallel exploration. The Librarian fires ~8 tool calls in parallel per turn, up from ~3 with Sonnet, and wraps up a search in ~5 turns instead of ~15.
In our internal eval, about a quarter of that speedup comes from OpenAI's websocket mode and the rest from switching to GPT-5.5 with no reasoning:
| Sonnet-4.6 (medium) | GPT-5.5 (none) | |
|---|---|---|
| Latency (mean) | 237s | 81s (2.9x faster) |
| ↳ gain from websocket | — | ~1.3x |
| ↳ gain from model | — | ~2.2x |
| Quality (F1, mean) | 0.47 | 0.48 |
| Average cost | $1.21 | $0.69 |
Here's a comparison:
How does Kubernetes' HorizontalPodAutoscaler handle missing pod metrics when scaling down — does it assume missing pods are at 100% of their resource requests, or 100% of the target utilization? Cite the function and logic in the source.
Sonnet 4.6 (left) took 2 minutes and cost $1.08, while GPT-5.5 (right) took 40 seconds and cost just $0.47.