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Elorian's first AI model wants to reason with images, not just about them

Palo Alto startup Elorian released its first AI model, Glimpse, on Friday as a research preview with API access, priced at $0.60 per million input tokens and $3 per million output tokens. Glimpse uses a "visual scratch space" that lets the model crop into image regions, pull specific video frames, or run code mid-reasoning, and Elorian says it outperforms GPT-6 Astra on scientific chart reasoning and short-form video captioning despite being trained on a few hundred GPUs. Elorian, which raised a $55 million seed round at a $300 million valuation co-led by Striker Venture Partners, Menlo Ventures and Altimeter Capital with participation from Nvidia and Google chief scientist Jeff Dean, is targeting robotics firms, scientific labs, and media companies, with CEO Andrew Dai saying the company aims next year to build "the world's best visual reasoning model.

by read2 min views1 publishedOct 16, 2026
Elorian's first AI model wants to reason with images, not just about them
Image: TechCrunch AI

Elorian, the Palo Alto AI startup that raised a $55 million seed round at a $300 million valuation before it launched a product, released its first model on Friday, TechCrunch has exclusively learned.

The model, Glimpse, is launching as a research preview with API access and a chat interface is waitlist-only, so for now it’s a results table and a thesis. The thesis? Today’s AI models, for all their skill with language and code, still can’t really see.

Most multimodal models look at an image once, convert it to tokens, and then reason about it in text — like describing a photo from memory. Glimpse keeps going back to the source. Mid-reasoning, it can crop into a region, pull specific frames from a video, or run code to measure or compare what it’s looking at, a mechanism Elorian calls a “visual scratch space.” Think of someone pinching to zoom on a phone photo to double-check what they thought they saw.

For former Google DeepMind researcher and Elorian CEO Andrew Dai, one of the clearest signs that AI still couldn’t really see came on game night. Last year he photographed a board game he’d just finished with friends and asked a frontier model who was winning. It couldn’t say. Board games “each have their own visual language, each have their own iconography, symbols,” he told TechCrunch. “To an adult, it’s quite easy to understand what’s going on with minimal text, but these models aren’t able to intuit what the symbols mean.”

“Humans can look at IKEA diagrams, with no text, and assemble IKEA furniture, right? Why can’t AI models?” he said.

The approach isn’t completely new — OpenAI added crop-and-zoom during reasoning to its o-series models in 2025 — but Elorian’s pitch is that it built the whole model around it, cheaply. The company says a small team trained Glimpse on a few hundred GPUs and that the model is substantially smaller than the frontier systems it’s benchmarked against.

Glimpse costs $0.60 per million tokens in and $3 per million tokens out — cheaper than mid-level models like Sonnet and Sol but more expensive than lightweight models like Haiku and Luna.

But according to Elorian’s evaluations, Glimpse outperforms even GPT-6 Astra on scientific chart reasoning and short-form video captioning, with competitive results on other visual reasoning tasks.

Elorian came out of stealth six months ago with a round co-led by Striker Venture Partners, Menlo Ventures and Altimeter Capital, with participation from Nvidia and Google chief scientist Jeff Dean.

The initial targets are companies sitting on lots of video: robotics firms, scientific labs, media and creative companies. Longer term, Elorian wants to move from seeing to doing. That means building a model of a scene using that to choose an action, including directly controlling robots. Next year, Dai said, the company aims to build “the world’s best visual reasoning model,” one that leads on every visual reasoning test.

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