dots.vlm1
RedNote's first open vision-language model - DeepSeek V3 backbone with a from-scratch 1.2B vision encoder.
About
dots.vlm1 is the first vision-language model in RedNote HiLab's dots family, from the team behind the Xiaohongshu social platform. It pairs a 1.2-billion-parameter NaViT vision encoder, trained entirely from scratch with dynamic resolution support, with the DeepSeek V3 large language model as its language backbone.
The model was trained with heavy synthetic multimodal data - tables, charts, documents, and interleaved web content - to push visual perception and reasoning, particularly OCR. RedNote positions it as setting a new ceiling for open-source vision-language models while staying competitive on pure-text tasks.
Honest limits: the headline results are from RedNote's own evaluation suite, not independent benchmarks. The release date here is era-level (2025), flagged honestly. License details should be checked on the official repository and model card.
Specs
Context window
Pricing
Free quota
API access
Weights
Released
Benchmarks
Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.
Use cases
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 88; Trending score 76/100 from researcher assessment.