01What Is Toast 1 and How It Works

Toast 1 is a new AI model from Mixed Bread that is trained specifically to search. It does not try to do everything. It does one thing: find evidence.

Really fast. In Prime Intellect's tests, it reaches strong retrieval quality in 8–10 seconds. The next frontier model takes about 85 seconds.

That is up to 12x faster.

Instead of having a frontier model search through documents — burning expensive compute time — Toast 1 handles the whole search loop. It breaks your question into subqueries, searches in parallel, inspects what it finds, decides what is missing, searches again, filters and ranks the evidence, and then sends a clean, curated context package to the downstream reasoning model. The frontier model never has to touch the search loop.

It just gets the evidence — already filtered and ranked — ready to reason on.

02Main Features of Toast 1

Toast 1 offers three big features. First, it is 12x faster than frontier models for retrieval tasks. Second, it costs about 1/10th of what frontier models cost.

Third, it delivers frontier-level retrieval quality in independent evaluations by Prime Intellect.

  • Subquery breakdown: Toast 1 automatically splits one question into many subqueries and searches in parallel.
  • Iterative refinement: It inspects results, decides what is missing, and searches again until it has enough evidence.
  • Filter and rank: It removes noise, ranks evidence by relevance, and passes only the best context to the reasoning model.

These features mean the expensive reasoning model never has to do the repetitive, high-volume search work. That speeds up the entire pipeline and saves money.

03How to Set Up Toast 1 in Your Workflow

Setting up Toast 1 takes a few steps. You need a reasoning model partner (like GPT 5.6 Sol) and a clear prompt. Here is how to get started:

  1. Get access to Toast 1. Go to the Mixed Bread website or platform where the model is hosted. Sign up or request API access.
  2. Choose a reasoning model. Pick a frontier model to pair with Toast 1 — for example, GPT 5.6 Sol or Claude Fable 5.
  3. Write a prompt. Tell Toast 1 exactly what to search for and how to filter. Example: "Find every major AI automation tool released in the last 24 hours. Pull the ones most relevant to business owners. Filter out developer-only tools. Return top 10 with one-line summaries."
  4. Run the search. Send the prompt to Toast 1. It will break the query into subqueries, search in parallel, and return a curated evidence package.
  5. Pass to reasoning model. Send the evidence package to your reasoning model. It will format the output (for example, a daily briefing) without doing any search itself.
  6. Automate. Schedule daily research sweeps by connecting Toast 1 to a scheduler like Cron or an automation tool. Set it to run every 24 hours.

04How to Use Toast 1: A Real Workflow Example

Here is a practical example from the episode. Say you run the AI Profit Boardroom and want a daily research sweep for members. You give Toast 1 this prompt: "Find every major AI automation tool released in the last 24 hours.

Pull the ones most relevant to business owners who want to save time and get more customers. Filter out anything that is developer only or too technical for a non-coder. Rank by relevance and return the top 10 with a one-line summary of each."

  • Toast 1 searches in parallel across multiple sources — news sites, blogs, product pages.
  • It filters noise automatically. It removes developer-only tools and keeps only business-relevant ones.
  • It ranks the top 10 and writes a one-line summary for each.
  • It hands the curated list to your reasoning model. That model formats it into a daily member briefing.

Your members wake up each morning with the most relevant AI tools and updates already curated and ready. No manual research. No tab overload.

Fully automated. That saves hours every day.

05Results and Benchmarks from the Episode

Prime Intellect, Mixed Bread's training partner, ran evaluations. Toast 1 reached strong retrieval quality in about 8–10 seconds. The next frontier comparison point took about 85 seconds. That is up to 12x faster.

They also paired Toast 1 with GPT 5.6 Sol as the reasoning model and tested it against Claude Fable 5 on Office Q, a benchmark for multi-document, knowledge-intensive questions. The Toast 1 + GPT 5.6 Sol combination beat Claude Fable 5 by nearly 10 percentage points at just 27% of the cost.

These numbers come from Mixed Bread and Prime Intellect's own evaluations. Independent testing is still catching up. But the direction is clear: a specialized search agent paired with a reasoning model can outperform one of the most capable all-in-one frontier models on real business tasks.

06Tips, Limits, and Mistakes to Avoid

Tip: Always write specific prompts. Tell Toast 1 exactly what to search for, what to filter, and how to rank. Vague prompts give messy results.

Use the example prompt from section 4 as a template.

Limit: Toast 1 is a search-only model. It cannot do reasoning, writing, or formatting. You must pair it with a reasoning model for output.

Use GPT 5.6 Sol, Claude Fable 5, or another frontier model.

Mistake to avoid: Do not use Toast 1 for tasks that require creative writing or complex decision-making. It is trained exclusively to find evidence. If you ask it to "write a blog post," it will search for existing posts instead of writing one.

Warning about benchmarks: Most evaluation numbers come from Mixed Bread and Prime Intellect themselves. Independent tests are still coming. Be cautious with the claims until third parties confirm them.

07Who Toast 1 Is For and Why It Matters

Toast 1 is for business owners, researchers, and teams who run research workflows across documents, PDFs, Slack threads, and enterprise knowledge bases. It is also for anyone building automated research pipelines, content systems, or lead generation workflows with AI.

It matters because AI is moving toward specialized agents that each do one job really well — instead of one giant model doing everything average. Toast 1 is Mixed Bread's first move in that direction. It saves time and money by letting the expensive reasoning model focus on reasoning, while Toast 1 handles all the search grunt work.

If you want to automate research content and lead generation, Toast 1 can be the search engine inside your AI system. It runs daily sweeps, filters noise, and hands curated evidence to your reasoning model. That gives you hours back every day.