Unverified50% confidenceBenchmarkExact time
In 18 real user sessions, Agile Deliberation improved the F1 score of the Gemini-based classifier by 10.5 points compared with the zero-shot baseline.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
11/5/2026
First Seen
Valid until: 2/3/2027
Sources
Related Entities
Related Claims
UnverifiedGemini fourth-generation Carbon was announced on October 28, strengthening long-horizon coding and security remediation capabilities, with an official intelligence index score of 59, introductory pricing of $2 per million input tokens and $10 per million output tokens, and currently limited availability to defenders and trusted partners.65% similarUnverifiedThe Gemini API free tier has a quota of 0 for Pro-series models such as gemini-3.1-pro-preview, returning limit: 0, and it remains 0 after the daily reset, so waiting to retry is pointless.62% similarUnverifiedThe course hands-on project uses the Gemini embedding model to generate vectors, and the core call is client.models.embed_content, passing in the model name (such as gemini-embedding-001).62% similarUnverified10 decision models matched or exceeded the accuracy of the Gemini 2.5 Flash used in the paper (61.3%), while costing 4–39 times less to bill (2 of them free) and having 2.6–6.0 times lower latency.62% similarUnverifiedGemini 1.5 Pro通过Multi-Query Attention等技术优化了长上下文下的推理效率61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1138833API
curl https://kongchang.com/api/v1/knowledge/claims/1138833MCP
get_claim(id=1138833)