---
title: "K-Dense Web Office Hours: Q&A Recap (April 17, 2026)"
description: "Key takeaways from our April 2026 Office Hours covering open source model support, research workflows, model performance, platform comparisons, and enterprise deployment."
publishedAt: "2026-04-19"
tags: ["Product", "Community"]
canonical: "https://k-dense.ai/blog/office-hours-recap-april-2026"
---
Thank you to everyone who joined us for our live K-Dense Web Office Hours on April 17th!

This intimate session brought a great mix of questions: from researchers looking to streamline manuscript writing, to teams navigating petabyte-scale data, to users eager to run K-Dense with open source models.

Here were the highlights from the conversation:

## Open Source Model Support

| *Question* | *Answer* |
| :--- | :--- |
| **Will K-Dense BYOK support open source models like those available through Ollama?** | Yes, open source model support is on the roadmap. The update will include a UI option to select between models. The main challenge is that many open source models still struggle with reliable skill calling and activation, which is critical for K-Dense's agent workflows. |
| **Which open source models are recommended for testing?** | The team sees Qwen 3.5, Qwen 3.6 (released just yesterday), and Gemma 4 as the best current options for skill-capable open source use. |
| **Can I use different models for different agent roles?** | Yes. K-Dense's architecture will support this kind of model routing to allow role-based assignment of models to agents. |

## Model Performance Comparison

| *Question* | *Answer* |
| :--- | :--- |
| **Which models perform best for Scientific Agent Skills on the platform?** | Claude Opus and GPT-5.4 are currently the top performers for Scientific Agent Skills. |
| **What about OpenAI's new GPT Rosalind model for life sciences?** | GPT Rosalind is a promising new life sciences–focused model from OpenAI. It's currently in closed access, but it represents a good direction with domain-specific fine-tuning. |

## Platform Comparisons

| *Question* | *Answer* |
| :--- | :--- |
| **How does K-Dense Web compare to Claude CoWork?** | Claude CoWork is a work companion that connects to apps and summarizes emails and Slack, and it's great for day-to-day productivity. K-Dense Web is the knowledge work component for end-to-end research, providing research-backed citations, dataset analysis, and code generation with an interdisciplinary approach (as opposed to specialized tools like Kosmos). |
| **What are K-Dense Web's key strengths over other platforms?** | K-Dense Web handles very long context outputs and provides comprehensive analysis combining multiple disciplines. The multiagent architecture acts like a consulting firm, bringing diverse expertise to a problem. |

## Enterprise and Technical Considerations

| *Question* | *Answer* |
| :--- | :--- |
| **Can K-Dense Web handle petabyte-scale datasets?** | Large datasets at petabyte scale remain a challenge. MCP server integration is available but introduces latency issues at that scale. For enterprise customers with this need, K-Dense offers local deployment options. |
| **What does the enterprise deployment process look like?** | The team provides custom cost solutions based on requirements. Implementation timelines range from weeks to months depending on complexity, and a hardware deployment option is available to reduce IT approval cycles. |
| **Does K-Dense Web have memory or a knowledge base that persists between sessions?** | There is no memory system between sessions at this time. The team is considering a file system–based knowledge base and is waiting for stronger memory implementations from the broader industry before committing to an approach. |

Thanks again to everyone who attended this month's office hours. We love hearing directly from the community, and your questions continue to shape the direction of K-Dense Web.

Stay tuned for details on our next Office Hours event on May 20. Register now on [Luma](https://luma.com/5tylggtt).