Cypris Q Gets a Major Context Upgrade
We’ve rolled out a major upgrade to how Cypris Q manages context across complex research workflows, cutting context usage by up to 50% across the majority of sessions.
Cypris now uses context more intelligently across images, websites, tool calls, source analysis, and Q’s internal planning. The result is more focused reasoning, less unnecessary processing, and fewer credits required to execute complex research.
Importantly, this does not reduce the number of patents, papers, or other sources Q can analyze. Instead, Q is using less context on unnecessary intermediate steps, leaving more capacity for the research itself.

More Efficient Context Across Every Session
The latest upgrade improves how Q decides what information to keep active, what to compact, and what to retrieve only when needed.
Across our internal data, these changes have reduced context usage by up to 50% for 75% of Cypris sessions. That gives Q more room for deeper analysis while improving the efficiency and cost of running sophisticated research workflows.
For users, that means longer sessions, more efficient execution, and less credit consumption on complex tasks.
Infinite Session Length
Q can now automatically compact long conversations while preserving the history of your research.
A dedicated Transcript subagent can retrieve exact details from earlier in the session when needed, allowing users to continue working across extended research workflows without losing access to prior discussion.
Deeper Source Analysis
A new Source Analysis subagent can read and reason across the full text of individual sources.
This gives Q more complete context when analyzing technical documents and allows it to go deeper into the underlying source material rather than relying only on limited excerpts.
Smarter Internal Planning
We’ve also improved how Q plans complex research tasks.
Q now builds more efficient research plans, using the tools and analysis required for the task without taking unnecessary steps. This improves reasoning quality while reducing unnecessary token and credit usage.
Optimized Web, Image, and Tool Context
Cypris now uses context more efficiently when working with:
- Websites and individual pages
- Images
- Tool calls and outputs
- Source analysis
- Q’s internal planning
By reducing unnecessary context and processing across these areas, more of each session can be devoted to meaningful analysis.

Lower Credit Consumption for Complex Research
These infrastructure improvements also translate directly into more efficient credit usage.
Complex research workflows can now require materially fewer Cypris credits to complete because Q is processing less unnecessary context while preserving the information it needs to perform the task.
Built for Longer, Deeper Research
The goal is simple: help researchers run longer, deeper, and more complex tasks in Cypris without the context limitations or unnecessary compute of general-purpose AI systems.
More improvements are already planned, including greater visibility into Q’s planning process and dedicated infrastructure for research across a wider array of documents.
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