Speech
Transcribe recordings or generate a voice. Compare language coverage, latency, intelligibility, and deployment.
CodeSOTA / AI task routing
Start with the work you need done. Compare models across quality and cost, inspect the evidence, and use a common API to choose a route.
Available today: model selection across the registry and an execution API for code & text. Document, speech, and vision execution are planned.
Choose a task, compare actual benchmark observations, and inspect the Pareto frontier before selecting a route.
Benchmark tradeoffs
Every dot is a recorded result. Highlighted models have no competitor in this cohort that is at least as good on both axes and strictly better on one.
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01 / Define the work
Registry selection only · execution planned
Target outputs describe the task. This preview returns model recommendations. It does not process your files or run inference.
Explore documents evidence →02 / Inspect the shortlist
03 / Use the same selection API
curl 'https://www.codesota.com/api/pareto-router?task=document-ocr&objective=balanced&limit=3'The product we are building
Our direction is a common API and account across AI tasks, with versioned recipes and a stable output contract for each task. Switch the model behind document parsing, transcription, voice generation, or code without rewriting your application.
Explore the router →First expansion / Documents
Turn scans and PDFs into text, tables, or structured fields. Choose for your documents, language, and deployment.
Explore OCR & document AIWorking with Polish documents? See Polish OCR evidence →
Compare the tools you are considering.
Explore the task guides and evidence behind future speech routes and the existing coding API.
Transcribe recordings or generate a voice. Compare language coverage, latency, intelligibility, and deployment.
Generate functions or repair a repository. Compare models and agents on evidence that matches the work.
Describe your task, language, budget, or hardware to search CodeSOTA’s guides and registry.
Evidence behind the choice
A strong result on one test does not guarantee a fit for your documents, recordings, or repository. Check the model version, evaluation protocol, source, and deployment requirements. Then test representative examples.
How to read our evidence →More tasks, model results, and research when you need to go deeper.
Explore the wider catalogue, from embeddings to computer vision.
Inspect results, metrics, sources, and evaluation protocols.
Look up a model and the evidence recorded for it.
Follow original experiments and the claims they support.