BlogLLM Benchmark Scores as Published, Side by Side

OCR-Reasoning: Results as Published

Every result the catalog holds for OCR-Reasoning: 5 models from 4 developers, read from 1 page. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.

Area Multimodal UnderstandingMaintainer OCR-Reasoning authorsIntroduced 2025Data version 2026103001, as of 2026-10-30

OCR-Reasoning tests reasoning over text-rich images such as documents, charts, receipts and screenshots: the answer needs both reading the text and reasoning about it (calculation, logic, spatial and multidisciplinary knowledge). The score is accuracy.

Not checked against a maintainer's page.

OCR-Reasoning

ModelValuePrinted bySetup as printed
Qwen3.5-122B-A10BAlibaba, released 2026-02-2464.3%NVIDIA, NVIDIA Nemotron 3.5 Super VL 120B-A12B model cardchecked 2026-10-19-
Qwen3.8-Flash-NextAlibaba67.1%NVIDIA, NVIDIA Nemotron 3.5 Super VL 120B-A12B model cardchecked 2026-10-19-
GLM-5.3-FlashZ.ai, released 2026-08-2664.6%NVIDIA, NVIDIA Nemotron 3.5 Super VL 120B-A12B model cardchecked 2026-10-19-
Nemotron 3.5 Super VL 120B-A12BNVIDIA, released 2026-10-1565.08%NVIDIA, NVIDIA Nemotron 3.5 Super VL 120B-A12B model cardchecked 2026-10-19-
Inkling-SmallThinking Machines54.7%NVIDIA, NVIDIA Nemotron 3.5 Super VL 120B-A12B model cardchecked 2026-10-19-

Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.