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PRACTICAL WORKFLOW / 02

Research a company.

Turn source material into a brief you can check and act on.

A model is not a search engine. Supply current sources or use an app with browsing, then open every cited link.

Three ways to choose.

Explore matching models ↗

These are automated capability-based shortlists, not Enterprise DNA tested recommendations. Candidates require text support and at least 32,000 context tokens. Preview, experimental, batch and free variants are excluded. Cost picks require non-zero listed rates. Published index scores are a guide, not proof of task completion.

Published benchmark leader

No matching measurement is available. Explore the catalogue and test a candidate on your own sample.

Lowest estimated API cost

DeepSeek logo

DeepSeek R1 0528 Qwen3 8B ↗

Lowest listed cost for 10,000 input and 2,000 output tokens. Output quality and retries can change the final cost.

Input / 1M tokens
$0.060
Output / 1M tokens
$0.090
Example task estimate
$0.00078 USD
Price record
2026-07-13
Check source & availability ↗

API estimates exclude caching, tools, reasoning overhead, retries and provider fees. Access through a chat app or subscription has its own pricing and capabilities.

GET A USEFUL RESULT

Your first run.

  1. Gather current public sources and record their dates.
  2. Ask for a brief that links every factual claim to a source.
  3. Check the sources and mark gaps before sharing.

A prompt to start with.

Using only the sources below, write a company brief covering its offering, customers, recent developments and open questions. Cite the source URL and date for each factual claim. Separate facts from inference. Do not invent revenue, customers or quotations. If a source does not support a claim, say so.

[Paste source URLs, excerpts and dates here.]

MAKE YOUR OWN COMPARISON

Same task. Same evidence. Better decision.

Try the same redacted sample and prompt with two models. Record whether each result is correct, how much editing it needs, elapsed time and total cost including retries. Keep the outputs alongside your expected answer. Choose the model that completes your work reliably.

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