Qwen3.5 27B tops OCR redaction tests
Qwen3.5 27B looks like a strong open-weight VLM that can slot into a real redaction workflow on a 24GB GPU. It handles difficult handwriting and custom-entity redaction well, but face masking and missed lines still make human review mandatory.
Qwen3.5 27B is good enough to be useful, but not good enough to be trusted blindly. That’s the real story here: local redaction has moved from demo territory into a productive human-in-the-loop workflow.
- –Handwritten OCR is the clearest win, with better word capture and bounding boxes than smaller Qwen variants.
- –Custom-entity redaction is a strong fit because it leans on semantic span finding more than perfect page layout.
- –Dense pages still trigger skipped lines, so omissions remain the main failure mode.
- –Face redaction is still fragile because detection succeeds more often than full coverage.
- –The best workflow is hybrid: deterministic extraction first, PaddleOCR for easy text, Qwen3.5 27B for the hard leftovers.
- –At 4-bit quantization, the model finally lands in the consumer-GPU sweet spot that makes local redaction practical.
DISCOVERED
125d ago
2026-03-29
PUBLISHED
125d ago
2026-03-28
RELEVANCE
AUTHOR
Sonnyjimmy