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var(--line);border-radius:16px;padding:26px 24px;box-shadow:var(--shadow);display:flex;flex-direction:column;gap:16px;}\n.psvr-scope .tmn .tmn-q{color:var(--ink);font-size:14.5px;flex:1;white-space:pre-line;}\n.psvr-scope .tmn .tmn-q::before{content:\"\\201C\";color:var(--brand);font-size:28px;font-family:Georgia,serif;line-height:0;display:block;margin-bottom:6px;}\n.psvr-scope .tmn .tmn-who{display:flex;flex-direction:column;gap:2px;border-top:1px solid var(--line);padding-top:14px;}\n.psvr-scope .tmn .tmn-name{font-weight:700;font-size:13.5px;color:var(--ink);}\n.psvr-scope .tmn .tmn-role{font-size:12.5px;color:var(--ink-faint);}\n\n\/* ---------- Feature grid (long-form) ---------- *\/\n.psvr-scope .featuregrid{display:grid;grid-template-columns:repeat(3,1fr);gap:20px;margin-top:8px;}\n@media (max-width:900px){.psvr-scope .featuregrid{grid-template-columns:1fr 1fr;}}\n@media (max-width:600px){.psvr-scope .featuregrid{grid-template-columns:1fr;}}\n.psvr-scope .feat{background:var(--bg);border:1px solid var(--line);border-radius:14px;padding:24px 22px;box-shadow:var(--shadow);}\n.psvr-scope .feat .feat-ic{width:36px;height:36px;border-radius:10px;background:var(--brand-glow);color:var(--brand-deep);display:flex;align-items:center;justify-content:center;margin-bottom:14px;}\n.psvr-scope .feat .feat-ic svg{width:18px;height:18px;}\n.psvr-scope .feat h4{font-size:15.5px;font-weight:700;margin-bottom:9px;color:var(--ink);}\n.psvr-scope .feat p{font-size:13.5px;color:var(--ink-soft);}\n\n<\/style><div class=\"psvr-scope\"><div class=\"herowrap\"><div class=\"pagehead\"><div class=\"wrap\"><div class=\"pagehead-grid\"><div><div class=\"crumb\">Parashift<span>\/<\/span>Comparisons<span>\/<\/span>Parashift vs. OpenAI<\/div><span class=\"eyebrow\">Comparison \u00b7 OpenAI<\/span><h1>Parashift vs. OpenAI<\/h1><p class=\"lede\">Both run on language models. With Dokumentli\u00ae, Parashift uses its own vision language model built for one thing: business documents. The difference lies in the model class, in how it is operated, and in the platform around it.<\/p><div class=\"ctas\"><a class=\"btn\" href=\"\/en\/demo\/\">Book a demo<\/a><a class=\"btn ghost\" href=\"\/en\/dokumentli\/\">See Dokumentli<\/a><\/div><div class=\"microproof\"><span>88.4% cANLS@0.8 in our own benchmark<\/span><span>Runs on a single 24 GB GPU<\/span><span>Processing in CH, DE or the EU<\/span><\/div><\/div><div class=\"extractcard\"><div class=\"ec-top\"><span class=\"ec-id\">Benchmark 08\/2026 \u00b7 3368 documents<\/span><span class=\"ec-pill\">Measured<\/span><\/div><div class=\"ec-body\"><div class=\"ec-thumb\"><svg width=\"60\" height=\"76\" viewBox=\"0 0 60 76\" fill=\"none\">\n            <path d=\"M6 2h32l14 14v58a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2z\" fill=\"var(--bg-alt)\" stroke=\"var(--line)\" stroke-width=\"1.5\"><\/path>\n            <path d=\"M38 2v12a2 2 0 0 0 2 2h12\" fill=\"none\" stroke=\"var(--line)\" stroke-width=\"1.5\"><\/path>\n            <line x1=\"12\" y1=\"32\" x2=\"42\" y2=\"32\" stroke=\"#c7d0e0\" stroke-width=\"2.5\" stroke-linecap=\"round\"><\/line>\n            <line x1=\"12\" y1=\"41\" x2=\"42\" y2=\"41\" stroke=\"#c7d0e0\" stroke-width=\"2.5\" stroke-linecap=\"round\"><\/line>\n            <line x1=\"12\" y1=\"50\" x2=\"30\" y2=\"50\" stroke=\"#c7d0e0\" stroke-width=\"2.5\" stroke-linecap=\"round\"><\/line>\n            <line x1=\"12\" y1=\"60\" x2=\"36\" y2=\"60\" stroke=\"var(--brand)\" stroke-width=\"2.5\" stroke-linecap=\"round\"><\/line>\n          <\/svg><\/div><div class=\"ec-fields\"><div class=\"ec-row\"><span>Dokumentli\u00ae<\/span><b>88.4%<\/b><\/div><div class=\"ec-row\"><span>Gemini 3.6 Flash<\/span><b>83.5%<\/b><\/div><div class=\"ec-row\"><span>GPT-5.6 Sol<\/span><b>81.8%<\/b><\/div><div class=\"ec-row\"><span>Claude Opus 4.8<\/span><b>81.0%<\/b><\/div><\/div><\/div><div class=\"ec-foot\">cANLS@0.8 across five datasets, our own measurement<\/div><\/div><\/div><\/div><\/div><\/div><section><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">The real question<\/span><h2>Not whether a language model. Which one, where it runs, and what sits around it.<\/h2><\/div><p class=\"prozess-lead\">The question \u00abwhy not just use GPT for this\u00bb assumes an opposition that does not exist. Parashift works with a language model too. Dokumentli\u00ae is a small special-purpose vision language model, trained for exactly one job: classifying business documents and reading fields out of them.<\/p><p class=\"prozess-lead\">A general-purpose frontier model can do that as well. It can also write code, reason and produce prose. That breadth has a price: accuracy on documents, speed, cost per page, and the freedom to decide where processing happens.<\/p><p class=\"prozess-lead\">The difference sits on three levels. Which model does the work. Where it runs. And what else has to happen between document intake and the target system.<\/p><\/div><\/section><section class=\"alt\"><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">Three levels<\/span><h2>Where the difference actually sits.<\/h2><\/div><div class=\"featuregrid\"><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>A specialist, not a generalist<\/h4><p>Dokumentli\u00ae is trained on business documents and deliberately cannot do anything else. No open reasoning, no code, no conversation. That is why it is more accurate at its own job.<\/p><\/div><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>Measured, not claimed<\/h4><p>In our own benchmark from August 2026 across 3368 real business documents, Dokumentli\u00ae reaches 88.4% cANLS@0.8, ahead of Gemini 3.6 Flash at 83.5% and GPT-5.6 Sol at 81.8%.<\/p><\/div><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>Runs on your own hardware<\/h4><p>Dokumentli\u00ae runs on a single GPU with 24 GB of VRAM, on premise or in a private cloud. A hosted API service does not offer that choice.<\/p><\/div><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>Fix the processing location<\/h4><p>Switzerland, Germany or the EU, contractually assured. For banks, insurers and hospitals that is the condition under which a project starts at all.<\/p><\/div><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>A platform, not an endpoint<\/h4><p>Separation and classification come before extraction, then confidence checks, validation against master data and handover to the target system. A model call covers one of those steps.<\/p><\/div><div class=\"feat\"><div class=\"feat-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"3\" width=\"16\" height=\"18\" rx=\"1.5\"><\/rect><path d=\"M8 8h8M8 12h8M8 16h5\"><\/path><\/svg><\/div><h4>Evidence chain per field<\/h4><p>It is logged which document and which page a value came from, how certain it was and who corrected it. That is the basis for audit.<\/p><\/div><\/div><\/div><\/section><section><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">Where each fits<\/span><h2>Which model is right when.<\/h2><\/div><div class=\"flow\"><div class=\"step\"><div class=\"n\">01 \u00b7 REASONING<\/div><h4>Frontier model<\/h4><p>Reasoning, code, open conversation, creative writing. Dokumentli\u00ae is not built for any of that.<\/p><\/div><div class=\"arrow\"><svg width=\"20\" height=\"20\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\"><path d=\"M5 12h14M13 6l6 6-6 6\"><\/path><\/svg><\/div><div class=\"step\"><div class=\"n\">02 \u00b7 ONE-OFF<\/div><h4>Frontier model<\/h4><p>One stack, one analysis, no audit duty. Fast and without setup.<\/p><\/div><div class=\"arrow\"><svg width=\"20\" height=\"20\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\"><path d=\"M5 12h14M13 6l6 6-6 6\"><\/path><\/svg><\/div><div class=\"step\"><div class=\"n\">03 \u00b7 DOCUMENT STREAM<\/div><h4>Dokumentli\u00ae<\/h4><p>Daily throughput, identical results, confidence, handover to the core system.<\/p><\/div><div class=\"arrow\"><svg width=\"20\" height=\"20\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\"><path d=\"M5 12h14M13 6l6 6-6 6\"><\/path><\/svg><\/div><div class=\"step\"><div class=\"n\">04 \u00b7 REGULATED<\/div><h4>Dokumentli\u00ae<\/h4><p>Processing location, evidence and logging are part of the requirement.<\/p><\/div><\/div><\/div><\/section><section class=\"alt\"><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">Side by side<\/span><h2>General-purpose frontier model and Parashift with Dokumentli\u00ae.<\/h2><\/div><div class=\"cmp-wrap\"><table class=\"cmp\"><thead><tr><th>Task<\/th><th class=\"crit\">General-purpose frontier model<\/th><th class=\"good\">Parashift with Dokumentli\u00ae<\/th><\/tr><\/thead><tbody><tr><th>Classify business documents and extract fields<\/th><td class=\"crit\">Possible, at lower accuracy<\/td><td class=\"good\">Core task, trained for it<\/td><\/tr><tr><th>Accuracy in our benchmark 08\/2026<\/th><td class=\"crit\">GPT-5.6 Sol: 81.8% cANLS@0.8<\/td><td class=\"good\">Dokumentli\u00ae: 88.4% cANLS@0.8<\/td><\/tr><tr><th>Open reasoning, code, conversation<\/th><td class=\"crit\">Core task<\/td><td class=\"good\">Not provided for<\/td><\/tr><tr><th>On-premise operation<\/th><td class=\"crit\">Not provided for<\/td><td class=\"good\">A single GPU with 24 GB VRAM<\/td><\/tr><tr><th>Fixing the processing location<\/th><td class=\"crit\">Depends on the provider<\/td><td class=\"good\">Switzerland, Germany or the EU<\/td><\/tr><tr><th>Splitting stacks into documents<\/th><td class=\"crit\">Not provided for<\/td><td class=\"good\">Part of the processing<\/td><\/tr><tr><th>Confidence value per field<\/th><td class=\"crit\">No calibrated value<\/td><td class=\"good\">Per field, with a threshold<\/td><\/tr><tr><th>Evidence for audit<\/th><td class=\"crit\">No per-field log<\/td><td class=\"good\">Document, page, timestamp per value<\/td><\/tr><tr><th>Cost at high volume<\/th><td class=\"crit\">Grows with every token<\/td><td class=\"good\">Calculable per page or per node<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/section><section><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">The benchmark<\/span><h2>Our own measurement, August 2026.<\/h2><\/div><div class=\"effektband\"><div class=\"effekt\"><div class=\"num\">88.4%<\/div><p>cANLS@0.8, highest of seven models tested<\/p><span class=\"src\">Parashift benchmark 08\/2026<\/span><\/div><div class=\"effekt\"><div class=\"num\">3368<\/div><p>real business documents across five datasets<\/p><span class=\"src\">Parashift benchmark 08\/2026<\/span><\/div><div class=\"effekt\"><div class=\"num\">24 GB<\/div><p>of VRAM are enough for production use<\/p><span class=\"src\">Dokumentli\u00ae data sheet<\/span><\/div><\/div><\/div><\/section><section class=\"alt\"><div class=\"wrap\"><div class=\"hubcard\"><div><h3>Not an either-or.<\/h3><p>Many customers use both: a frontier model for analysis, reasoning and text work, Dokumentli\u00ae for the document stream that has to reach the core system every day.<\/p><\/div><a class=\"btn ghost\" href=\"\/en\/document-ai-comparison\/\">See all comparisons<\/a><\/div><\/div><\/section><section class=\"alt\"><div class=\"wrap\"><div class=\"section-head\"><span class=\"eyebrow\">Frequently asked<\/span><h2>Questions about this comparison.<\/h2><\/div><div class=\"faqlist\"><details class=\"qa\"><summary>Is Parashift not just a language model as well?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">It is, and that is the point. Dokumentli\u00ae is a vision language model, but a small and specialised one. It is trained on business documents and deliberately cannot code or reason. That restriction is what makes it more accurate and cheaper at its own job than a generalist.<\/div><\/details><details class=\"qa\"><summary>Why would a smaller model be more accurate than GPT?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">Because the task is narrow. In our own benchmark from August 2026 across 3368 real business documents from five datasets, Dokumentli\u00ae reaches 88.4% cANLS@0.8 and GPT-5.6 Sol 81.8%. No model had seen the test documents before.<\/div><\/details><details class=\"qa\"><summary>What can Dokumentli\u00ae not do?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">Open reasoning, programming, general knowledge questions outside the document, and creative writing. A frontier model is the right tool for all of that, and we say so.<\/div><\/details><details class=\"qa\"><summary>Can we run the model ourselves?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">Yes. Dokumentli\u00ae runs on a single GPU with 24 GB of VRAM, on premise or in a private cloud. No document content leaves your environment.<\/div><\/details><details class=\"qa\"><summary>What is the difference between the model and the platform?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">The model reads a document. The platform first splits the stack, classifies per page, checks confidence values, validates against master data and hands over structured data to the target system. A model call alone covers one of those steps.<\/div><\/details><details class=\"qa\"><summary>How do costs behave at high volume?<span class=\"qa-ic\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"><path d=\"M6 9l6 6 6-6\"><\/path><\/svg><\/span><\/summary><div class=\"qa-a\">Token-based billing grows with page count and answer length. Parashift bills per page, or per node when you run it yourself. At several thousand documents a day that matters more than the price per call.<\/div><\/details><\/div><\/div><\/section><section class=\"finalcta\"><div class=\"wrap\"><h2>See the difference on your own documents.<\/h2><p>Book a no-obligation briefing: we run your documents through Dokumentli\u00ae and a frontier model and show the results side by side.<\/p><div class=\"ctas\"><a class=\"btn\" href=\"\/en\/demo\/\">Book a demo<\/a><\/div><p class=\"note\">Reply the same working day \u00b7 no sales pressure<\/p><\/div><\/section><\/div><script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Is Parashift not just a language model as well?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"It is, and that is the point. Dokumentli\u00ae is a vision language model, but a small and specialised one. 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