Gemini 3.5 Pro rumors point to stronger agent use
Leaked results suggest could rank ahead of major rival if the same results hold up in public testing. The main claims are a two-million-token , reasoning, and stronger agent support.
The biggest reported scores have not been officially published yet. The claimed improvement focuses on long reasoning, where a model must follow several connected steps, keep the original goal in mind, and catch mistakes before they affect the final answer.
Better long reasoning could help with coding, math, research, and planning work. Real value should be judged through practical , not benchmark claims alone.
Key points
- Leaked results claim could beat major rival models.
- The claimed features include a two-million-token , reasoning, and stronger agent support.
- The most dramatic benchmark scores have not been officially published.
- Long reasoning matters for coding, math, research, and planning tasks.
- Agent builders should wait for real workflow tests, pricing, speed, and failure-rate data.