Reducto 发布 r-1 单遍文档解析模型,错误率降 20%、每页 1 美分

内容摘要
Reducto近日发布了r-1单遍文档解析模型,这是基于全新架构构建的新一代解析模型,取代了公司原有的多阶段OCR。r-1在准确性、速度和成本方面均有显著提升,错误率降低了20%,每页成本降至1美分。该模型通过一次全页扫描即可完成OCR、布局检测、表格处理、格式化等任务,并支持数字文本、扫描和手写文本等多种格式。Reducto表示,r-1在内部评估中优于亚马逊Textract和Azure Document Intelligence等常用产品,以及大型LLM。此外,r-1还支持多租户云、客户VPC、本地部署和隔离安装,并符合SOC 2 Type II认证和HIPAA处理要求。
Reducto近日发布了r-1单遍文档解析模型,这是基于全新架构构建的新一代解析模型,取代了公司原有的多阶段OCR。r-1在准确性、速度和成本方面均有显著提升,错误率降低了20%,每页成本降至1美分。该模型通过一次全页扫描即可完成OCR、布局检测、表格处理、格式化等任务,并支持数字文本、扫描和手写文本等多种格式。Reducto表示,r-1在内部评估中优于亚马逊Textract和Azure Document Intelligence等常用产品,以及大型LLM。此外,r-1还支持多租户云、客户VPC、本地部署和隔离安装,并符合SOC 2 Type II认证和HIPAA处理要求。

Last week, Reducto announced r-1. It is the first model in a new parsing family built on a rewritten architecture, and it replaces the company’s multi stage agentic OCR with one full page pass. Reducto says r-1 is more accurate than its most powerful legacy agentic models, faster, and up to 6x cheaper.

Is it deployable today? Yes, in preview. r-1 runs through Reducto’s hosted Parse API on V3 and is switched on with a configuration flag. There are no open weights and no local checkpoint to self host. Reducto’s platform separately supports multi tenant cloud, customer VPC, on premises, and air gapped installs, with SOC 2 Type II attestation and HIPAA processing on higher tiers, per its security policies.

One pass instead of a pipeline

Legacy Parse runs OCR, layout detection, and post processing as separate stages, with optional agentic vision language passes layered on top. Each extra model call adds latency. r-1 folds text, tables, figures, layout, reading order, formatting, and grounding into a single full page pass. Every block returns with page relative bounding boxes that tie content back to its position on the page.

The consolidation is the real product claim. Teams working on financial statements, insurance claims, or contracts often route files across several providers and bolt on post processing to reach usable accuracy. r-1 targets that orchestration cost, not only raw character accuracy.

The numbers

Reducto reports a 20% reduction in error rate for the early r-1 preview against its own legacy agentic pipelines. It also states that r-1 outperformed commonly used hyperscaler products and large LLMs on complex documents in internal evaluations. Amazon Textract and Azure Document Intelligence are named in the release as the incumbent baseline category.

On price, legacy agentic models ran between 3 and 6 cents per page depending on workload. r-1 is 1 cent per page, all in, with no feature multipliers or credit costs layered on to reach high accuracy. Reducto frames this as part of a wider move to flat product rate cards.

Please note that the 20% error reduction is measured relative to Reducto’s own prior pipeline, not to a third party baseline. And the head to head against hyperscalers and LLMs is vendor run, with no public eval harness or dataset released alongside the announcement.

What r-1 resolves on the page

Per the documentation, r-1 handles the following natively in the full page pass: digital text, scans, and handwriting; table structure read with surrounding page context, including merged cells and nested headers; columns, headers, footers, sidebars, and reading order resolved together; figure detection with a short generated description; formatting that carries meaning, including headings, lists, bold, underlines, and strikethroughs; and grounding through page relative bounding boxes.

The long tail cases Reducto calls out are dense tables, unusual layouts, low quality scans, watermarked content, and documents that follow no predictable template. A dropped strikethrough can invert a contract clause, and a misread table can hand an agent the wrong figure, which is why these edge cases carry weight in regulated pipelines.

Migration path and what stays on the old stack

r-1 requires the V3 API. A Parse request that omits settings.model still runs on legacy Parse, so nothing breaks silently. New pipelines created in Studio default to r-1.

result = client.parse.run(
    input=upload.file_id,
    settings={"model": "r-1"}
)

Agentic processing is not gone. Workflows needing custom prompts or advanced chart extraction still route those pages through the agentic pipeline, which Reducto augments onto the r-1 result, and which adds latency. Teams migrating an existing configuration should check the r-1 configuration compatibility page first, since some legacy settings are ignored or unsupported.

Reducto has also signalled the next two pieces: r-1 mini for speed and cost sensitive workloads, and automatic per page routing that picks the right model for each page. Organisations moving off another parser can request up to $5,000 in credits for a side by side comparison.

Key Takeaways

  • r-1 collapses OCR, layout, tables, formatting, and grounding into one full page pass.
  • Reducto reports a 20% error reduction against its own legacy agentic pipelines.
  • Pricing drops from 3 to 6 cents per page to a flat 1 cent, all in.
  • Available in preview via the V3 Parse API using settings.model: "r-1", no open weights.

Check out the Reducto blog, Parse r-1 docs and announcement on X. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter. Wait! are you on telegram? now you can join us on telegram as well.

原始发布方:MarkTechPost(RSS)

原文时间:2026-09-08 11:07:15 +08:00

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