{"slug": "exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive", "title": "Exa Launches Agent Ultra: A Subagent Swarm Deep Research API Built for Exhaustive List Building", "summary": "Exa released Agent Ultra, the highest effort level of its Exa Agent API, which the company says beats Opus 5.5, GPT-6 Astra, and Perplexity Agent at maximum effort on 4 research benchmarks, including 81.4% soft recall on WANDR versus 72.3% for Opus 5.5 and 2,451 average passing entities per task on Company Find-All versus 146 for Opus 5.5. Agent Ultra is live today as a hosted API via the `effort: \"ultra\"` parameter, is not open weights, and cannot be self-hosted; runs typically finish complex tasks in about 30 minutes and can take up to 3 hours. Exa reports all results as vendor-reported and not yet independently reproduced, and cites cost claims including half of Opus 5.5's cost per task on WANDR and the lowest cost per entity found on Company Find-All.", "body_md": "[Exa](https://exa.ai/) has released **Agent Ultra**, the highest effort level of its [Exa Agent](https://exa.ai/products/agent) API. It is built for research that must run to exhaustion: large list building, entity enrichment, and questions that need thousands of sources. Exa team reports that Ultra beats Opus 5.5, GPT-6 Astra, and Perplexity Agent, each at maximum effort, on 4 research benchmarks.\n\n**Is it deployable?** Yes, as a hosted API. Agent Ultra is live today on the Exa API by setting `effort: \"ultra\"`. It is not open weights and cannot be self-hosted.\n\n## **What is Exa Agent Ultra?**\n\nExa Agent splits a task into subtasks and assigns subagents to research several domains at once. It routes frontier models to steps that need them and faster models where those are enough. Ultra is the mode that spends the most compute. According to the [Agent Ultra docs](https://exa.ai/docs/agent/agent-ultra), it runs longer than any other effort to return the most complete results.\n\nUltra runs typically finish complex tasks in about 30 minutes. Very hard tasks can take up to 3 hours.\n\n## **Benchmark Results**\n\nAll figures below are from [Exa’s launch post](https://exa.ai/blog/exa-agent-ultra). Competitors ran at their maximum effort setting.\n\n| Benchmark (metric) | Agent Ultra | Opus 5.5 | GPT-6 Astra | Perplexity Agent | \n|---|---|---|---|---|\n| WANDR (soft recall) | **81.4%** | 72.3% | 26.0% | 40.1% | \n| DeepSearchQA (F1) | **93.9%** | 77.6% | 85.3% | 89.7% | \n| WideSearch (row-level F1) | **58.9%** | 51.6% | 54.7% | 56.0% | \n| Company Find-All (avg. passing entities per task) | **2,451** | 146 | 113 | 98 | \n\n**Exa pairs each result with a cost claim:**\n\n- **WANDR:** +12.6% over Opus 5.5, at half its cost per task.\n- **DeepSearchQA:** +4.7% over Perplexity, at 46% lower cost per task than GPT-6 Astra.\n- **WideSearch:** +5.2% over Perplexity, at the lowest cost per task of the 4 systems.\n- **Company Find-All:** +1579% over Opus 5.5, at the lowest cost per entity found.\n\nThese gains are relative, not percentage points. On WANDR, the absolute gap to Opus 5.5 is 9.1 points.\n\n## **Understanding These Numbers**\n\n[WANDR](https://arxiv.org/abs/2608.14747) is Perplexity’s benchmark of 500 wide and deep data-collection tasks, with an [open harness](https://github.com/perplexityai/wandr). Exa’s grader shares the upstream evaluation logic. It swaps in Exa as the contents tool, changes transport logic, and uses gpt-6-luna as the judge. Where a vendor had published a result on this harness, Exa reports that figure. Otherwise, Exa ran the benchmark itself.\n\n[DeepSearchQA](https://www.kaggle.com/benchmarks/google/dsqa) is Google DeepMind’s 900-prompt multi-step search benchmark. [WideSearch](https://arxiv.org/abs/2508.07999) tests broad information gathering. Exa evaluated up to 200 tasks each for WANDR and DeepSearchQA, and 100 each for WideSearch and Company Find-All. Graded task counts vary by provider. All results are vendor-reported and not yet independently reproduced.\n\n## **Where Agent Ultra Fits**\n\n**Exa lists 3 target user groups:**\n\n- **Model providers:** assemble training data, such as every paper and repo implementing a given technique. Verify criteria like ‘released weights, not just an API’.\n- **Financial services:** build diligence market maps, run KYC research across filings and court records, and monitor portfolio signals.\n- **Go-to-market teams:** build account lists and enrich rows with judgment fields, each backed by a cited URL.\n\nUltra can also expand an existing list. Pass the rows you already have, and they are excluded from new results.\n\n## **API, Pricing, and Controls**\n\nUltra uses the standard Agent run endpoint. The request supports `outputSchema`, `input.data`, and streaming.\n\n``` python\nfrom exa_py import Exa\n\nexa = Exa()\nrun = exa.agent.runs.create(\n    query=\"Find all companies building browser automation tools in the United States.\",\n    effort=\"ultra\",\n)\nrun = exa.agent.runs.poll_until_finished(run.id, timeout_ms=3 * 60 * 60 * 1000)\nprint(run.stop_reason)\n```\n\n- **Pricing:** metered at standard[Agent usage rates](https://exa.ai/docs/admin/pricing) , up to a default $20 per run. Runs that finish early cost less.\n- **Budget:**`maxCostDollars` accepts $1 to $100.`maxDurationSeconds` accepts 300 to 10,800 seconds.\n- **Stopping:** a stop call ends a run early, keeps its results, and bills usage up to that point.\n- **Timeouts:** SDK polling helpers time out after 1 hour by default, so set a longer timeout or stream events.\n- **OpenAI compatibility:** on[/responses](https://exa.ai/docs/integrations/openai-sdk) , set`reasoning.effort: \"ultra\"` with streaming or background mode.\n\nYou can test it in the [Exa API Playground](https://dashboard.exa.ai/playground/agent).\n\n## **Comparison**\n\n## **Key Takeaways**\n\n- Agent Ultra is Exa Agent’s highest effort mode, live now via API.\n- It orchestrates parallel subagents and mixes frontier and faster models.\n- Exa reports top scores on WANDR, DeepSearchQA, WideSearch, and Company Find-All.\n- Runs cost up to $20 by default, adjustable from $1 to $100.\n- Typical runs take about 30 minutes, with a 3 hour ceiling.\n\nCheck out the [**Technical Details**](https://exa.ai/blog/exa-agent-ultra). All credit goes to the researcher of this project. Also, feel free to follow us on **[Twitter](https://x.com/intent/follow?screen_name=marktechpost)** and don’t forget to join our **[150k+ML SubReddit](https://www.reddit.com/r/machinelearningnews/)** and Subscribe to **[our Newsletter](https://magic.beehiiv.com/v1/f5e63dd4-5653-4f09-83e2-321a8b1ba526?email={{email}})**. Wait! are you on telegram? [now you can join us on telegram as well.](https://t.me/machinelearningresearchnews)\n\nNeed to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? [Connect with us](https://forms.gle/MJjjVDPS7whH8Ngs6)\n\nMichal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.", "url": "https://wpnews.pro/news/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive", "canonical_source": "https://www.marktechpost.com/2026/09/26/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive-list-building/", "published_at": "2026-09-26 08:04:08+00:00", "updated_at": "2026-09-26 08:29:36.159663+00:00", "lang": "en", "topics": ["ai-agents", "ai-search", "artificial-intelligence", "ai-products", "ai-tools"], "entities": ["Exa", "Agent Ultra", "Exa Agent", "Opus 5.5", "GPT-6 Astra", "Perplexity Agent", "WANDR", "DeepSearchQA"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive", "markdown": "https://wpnews.pro/news/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive.md", "text": "https://wpnews.pro/news/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive.txt", "jsonld": "https://wpnews.pro/news/exa-launches-agent-ultra-a-subagent-swarm-deep-research-api-built-for-exhaustive.jsonld"}}