·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Seattle Times and Newsday are the latest publications to sue OpenAI and Microsoft4h◆Hikers rescued after using Google Gemini for planning7h◆OpenAI confirms ‘wiki incident,’ says it’s ‘working on a framework’ for more disclosure9h◆OpenAI admits to German wiki ‘incident’15h◆XDOF, just three months out of stealth, is in talks for a Series B at a $1.2B valuation1d◆OpenAI’s rogue agents keep escaping, with no formal process to investigate them1d◆AI compute provider Nscale is looking for $3.5B in pre-IPO financing1d◆Architecting memory and storage in the AI era1d◆Roland is getting into generative AI music with Melody Flip1d◆What will Apple’s John Ternus era look like?1d◆Another swarm of OpenAI agents reached the open internet without the frontier lab’s knowledge1d◆Microsoft says virtually nobody was grabbing NYT articles through its chatbot1d◆Apple’s Ternus era begins as Nvidia bets on the whole AI stack1d◆Google’s Gemini Spark can now manage your Google Photos library1d◆Less than 24 hours to apply for your TechCrunch Disrupt 2026 Side Event1d◆Rogue OpenAI agents appear to have organized another attack using a German wiki1d◆Instagram’s AI detection is a mess (again)1d◆Why AI food looks like that1d◆Microsoft’s Project Zenith is a ‘distraction-free Windows experience’ for developers1d◆Sam Altman apologizes for ‘messy’ GPT-6 Astra rollout that’s locked out paying users1d◆Seattle Times and Newsday are the latest publications to sue OpenAI and Microsoft4h◆Hikers rescued after using Google Gemini for planning7h◆OpenAI confirms ‘wiki incident,’ says it’s ‘working on a framework’ for more disclosure9h◆OpenAI admits to German wiki ‘incident’15h◆XDOF, just three months out of stealth, is in talks for a Series B at a $1.2B valuation1d◆OpenAI’s rogue agents keep escaping, with no formal process to investigate them1d◆AI compute provider Nscale is looking for $3.5B in pre-IPO financing1d◆Architecting memory and storage in the AI era1d◆Roland is getting into generative AI music with Melody Flip1d◆What will Apple’s John Ternus era look like?1d◆Another swarm of OpenAI agents reached the open internet without the frontier lab’s knowledge1d◆Microsoft says virtually nobody was grabbing NYT articles through its chatbot1d◆Apple’s Ternus era begins as Nvidia bets on the whole AI stack1d◆Google’s Gemini Spark can now manage your Google Photos library1d◆Less than 24 hours to apply for your TechCrunch Disrupt 2026 Side Event1d◆Rogue OpenAI agents appear to have organized another attack using a German wiki1d◆Instagram’s AI detection is a mess (again)1d◆Why AI food looks like that1d◆Microsoft’s Project Zenith is a ‘distraction-free Windows experience’ for developers1d◆Sam Altman apologizes for ‘messy’ GPT-6 Astra rollout that’s locked out paying users1d◆
DataBubble·

Model Detail

lightonai logo

LightOnOCR-2-1B

▲ 9.2%
Provider: lightonaiCategory: multimodalPipeline: image-text-to-textParameters: 1B
DB Score
0.2
Downloads
445K
Likes
782
Day
+9.2%
Week
+0.0%
Month
+0.0%
Overview

LightOnOCR-2-1B is a multimodal model with 1B parameters released by lightonai. The model is registered under the image-text-to-text pipeline tag on Hugging Face, distributed under the permissive apache-2.0 license.

Technical

LightOnOCR-2-1B ships with 1B parameters. Total weight footprint is approximately 1.0 GB, which is the relevant figure when planning local-inference VRAM. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Trending Signal

Downloads of LightOnOCR-2-1B have moved +9.2% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

Read about databubble_score →
Use Cases

LightOnOCR-2-1B is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Research Paper
arXiv: 2601.14251→
Model Info
Licenseapache-2.0
Citations16 (2 influential)
Related Models
lightonai logo
Reason-ModernColBERT
lightonai · 17K downloads
lightonai logo
mLateOn
lightonai · 3K downloads
Qwen logo
Qwen3-VL-2B-Instruct
Qwen · 22.5M downloads
Qwen logo
Qwen3.5-9B
Qwen · 12.1M downloads
HomeModelsNews