Benchmark Results

Medieval Manuscripts

Evaluates models on page segmentation and handwritten text extraction from 15th century medieval manuscripts written in late medieval German. Tests the ability to transcribe historical handwriting, identify folio numbers, distinguish main text from marginal additions, and maintain historical spelling and formatting. Performance is measured using fuzzy string matching and Character Error Rate (CER).

Dataset Description Result Overview Test Runs

This benchmark has been run 221 times. It uses cer metric.

Tested providers: alibaba, anthropic, cohere, deepseek, genai, huggingface, mistral, openai, openrouter, scicore, x-ai

Tested models: GLM-4.5V-FP8, MiniMaxAI/MiniMax-M3:deepinfra, Qwen/Qwen3-VL-235B-A22B-Instruct:deepinfra, Qwen3.8-Flash-Next-FP8, claude-3-5-sonnet-20241022, claude-3-7-sonnet-20250219, claude-3-opus-20240229, claude-fable-5, claude-fable-5-1, claude-haiku-4-5-20251001, claude-opus-4-1-20250805, claude-opus-4-20250514, claude-opus-4-5-20251101, claude-opus-4-6, claude-opus-4-7, claude-opus-4-8, claude-opus-5, claude-opus-5-5, claude-sonnet-4-20250514, claude-sonnet-4-5-20250929, claude-sonnet-4-6, claude-sonnet-5, claude-sonnet-5-5, command-a-vision-07-2025, deepseek-flash, deepseek-v4-flash-vision-exp, gemini-2.0-flash, gemini-2.0-flash-lite, gemini-2.5-flash, gemini-2.5-flash-lite, gemini-2.5-flash-lite-preview-09-2025, gemini-2.5-flash-preview-09-2025, gemini-2.5-pro, gemini-3-flash-preview, gemini-3-pro-preview, gemini-3.1-flash-lite, gemini-3.1-flash-lite-preview, gemini-3.1-pro-preview, gemini-3.5-flash, gemini-3.5-flash-lite, gemini-3.6-flash, gemini-3.7-flash, gemini-3.8-flash, google/gemma-4-26b-a4b-it, google/gemma-4-31b-it, gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-4o, gpt-4o-mini, gpt-5, gpt-5-mini, gpt-5-nano, gpt-5.1-2025-11-13, gpt-5.2-2025-12-11, gpt-5.3-codex, gpt-5.4-2026-03-05, gpt-5.5-2026-04-23, gpt-5.6-luna, gpt-5.6-sol, gpt-5.6-terra, gpt-6-astra, gpt-6-luna, gpt-6-sol, grok-4.20-0309-reasoning, grok-4.3, grok-4.5, grok-4.6, grok-4.7, magistral-medium-2509, magistral-small-2509, meta-llama/llama-4-maverick, meta-llama/llama-4-scout, meta-models/Muse-Glimmer-30B:together, meta/muse-spark-1.2, meta/muse-spark-1.3, ministral-14b-2512, ministral-8b-2512, mistral-large-2411, mistral-large-2512, mistral-medium-2505, mistral-medium-2508, mistral-medium-3.5, mistral-small-2506, moonshotai/kimi-k3, o3, pixtral-12b, pixtral-large-2411, qwen/qwen3-vl-30b-a3b-instruct, qwen/qwen3-vl-8b-instruct, qwen/qwen3-vl-8b-thinking, qwen/qwen3.5-122b-a10b, qwen/qwen3.5-27b, qwen/qwen3.5-35b-a3b, qwen/qwen3.5-397b-a17b, qwen/qwen3.5-9b, qwen/qwen3.5-flash-02-23, qwen/qwen3.5-plus-02-15, qwen/qwen3.6-plus, qwen/qwen3.7-plus, qwen/qwen3.8-27b, qwen/qwen3.8-flash, qwen/qwen3.8-max, qwen/qwen3.8-max-0902, qwen3.5-122b-a10b, qwen3.5-27b, qwen3.5-35b-a3b, qwen3.5-397b-a17b, qwen3.5-flash-2026-02-23, qwen3.5-plus-2026-02-15, qwen35-397b-a17b-fp8, stepfun/step-3.7-flash, swiss-ai/Apertus-v1.5-70B:publicai, swiss-ai/Apertus-v1.5-8B:publicai, thinkingmachines/Inkling-Small:deepinfra, thinkingmachines/Inkling:together, x-ai/grok-4, z-ai/glm-5.3-flash, z-ai/glm-5v-turbo

• Type(s): manuscript
• Benchmark task(s):  transcription
• Writing: handwritten
• Source creation (century): 15
• Source Layout: prose
• Language(s): de