PaddleOCR-VL-1.6

Benchmarks 6 rows

Summary generated, cited

The model uses the PaddleOCRVLForConditionalGeneration architecture for tasks including document parsing, layout, table, formula, and chart analysis.^[1][2]

1. architectures
2. “document-parse, layout, table, formula, chart”

Generated 2026-10-07 15:16 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

What it is good at 6 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

• Understand images and videostructuraldecision-model estimate p=1.00name: VLtag: image-text-to-text+2 more
• Extract text from documentsstructuraldecision-model estimate p=1.00name: OCRtag: ocr
• Chat and follow instructionsstructuraltag: conversationalchat template present
• Read long documentsstructuralconfig: 131,072 context
• Work across languagesstructuraltag: multilingual
• Run on a laptop or phonestructuralfits: edge

Facts

• PaddleOCR-VL-1.6 has 959M parameters. (safetensors metadata, observed 2026-10-24)
• Context length is 131,072 tokens (128K). (config.json max_position_embeddings, observed 2026-10-24)
• License: Apache 2.0 (friction: none). Permissive; patent grant. (license file, observed 2026-10-24)
• Created 2026-05-27, last modified 2026-08-08. (HF API, observed 2026-10-24)

Servability

vLLM: supported · PaddleOCRVLForConditionalGeneration · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · PaddleOCRVLForConditionalGeneration · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit ESTIMATE

Weights-only memory for PaddleOCR-VL-1.6: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

Lineage

finetune: 14quantized: 22adapter: 4

Top variants (40 shown, ranked by downloads)

Repository changelog 19 commits

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.

Papers 1

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

• PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training this model
  Zelun Zhang, Hongen Liu, Suyin Liang +12 · 2026-06-02 · PDF · HF paper page (26 upvotes)

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Sources

• Hugging Face model repo
• HF Hub API (full)
• hub-stats parquet

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:43 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:16 UTC · Last verified 2026-10-25