Introducing Cura
Specialized 1T model for agentic healthcare, trained via recursive self-improvement for patient care, clinical reasoning, health administration, and long-running agentic healthcare workflows.
The strongest healthcare LLM — custom-built for your enterprise, owned by you
Cura is a one-trillion-parameter model built for the realities of enterprise healthcare. Post-trained from Kimi-K2.6 through recursive self-improvement, it is the strongest healthcare LLM today: it leads GPT-5.5, Claude Opus 4.8, and Gemini 3.1 Pro on five of the six benchmark panels that matter most in clinical and operational work.
Cura turns your institutional knowledge into an asset you own forever, one that gets smarter with every task your agents run. This is how healthcare organizations stop renting intelligence and start owning their agentic future.
Healthcare demands clinician-grade patient communication, expert reasoning over clinical text and images, and reliable execution against the real systems Payers and Providers run: core administrative processing, care management, network management, policy management, and CRM systems on the Payer side; EHRs, revenue cycle and practice management, ERP and finance, scheduling and workforce, and pharmacy systems on the Provider side. Cura 1T is built to serve all three. Its capabilities include:
Patient care
High-stakes patient communication: consultation, triage, and safety-conscious guidance. Trained with physician-authored rubrics, Cura communicates clearly, surfaces red flags, escalates when needed, and leads the frontier on physician-graded evaluations.
Clinical reasoning
Expert-level medical reasoning over clinical images. Cura works through specialty-board-level cases across 17 medical specialties and 11 body systems, and reasons natively over diverse clinical images, patient records, and examination results.
Healthcare agentic workflows
Interactive diagnosis and EHR workflow. Cura conducts multi-turn diagnostic dialogues (taking history, ordering tests, narrowing the differential) and drives FHIR tool calls against live EHR systems for Providers and core administrative processing systems for Payers.
Watch Cura work through each healthcare capability in a live demo:
Recursive self-improvement
Recursive self-improvement (RSI) is the idea of an AI system that improves its own capabilities, where each improvement makes it better at making further improvements. The output of one round becomes the engine of the next; that is what makes the process recursive rather than merely iterative.
Cura 1T trains through such a recursive loop. In each round, a training agent selects a target capability and trains the model using SFT, RL, and a continual learning method inspired by self-distillation (SDFT): we add a hint, let the model roll out the task on-policy with it, then train it to execute without the hint. The loop grades the benchmark trajectories, reads the failures, and refines the next data mixture from what it finds.
Building a model like this is as much a data-construction problem as a training problem. Healthcare offers thinner training signal than, say, a model for coding or math. Useful supervision sits scattered across guidelines, exams, images, and EHR and admin workflows. And adding examples for one behavior can erode another the model already got right. The loop's job is to find the missing data in the recipe, then prove, benchmark by benchmark, that each addition transfers without unnecessary forgetting. Reverted rounds stay in the record: they show which refinements transferred and which overfit a single benchmark.
Benchmarks
We evaluated Cura 1T on six healthcare panels spanning patient-facing response quality, expert clinical reasoning across text and images, and agentic execution against live EHR tooling. Cura 1T is the strongest model on five of the six panels and ranks second on the remaining one, MedXpertQA multimodal.
Healthcare
Patient care is where the loop moved the model furthest. On HealthBench Professional, Cura 1T's 66.2 is the strongest score of any frontier model, ahead of Claude Fable 5 (66.0) and more than ten points clear of Claude Opus 4.8 (55.8). On HealthBench Hard, the hardest physician-rubric panel, it scores 36.8: 5.3 points ahead of GPT-5.5 and a +14.6 jump over its Kimi-K2.6 base, whose failures were dominated by omitted rubric points rather than outright errors.
On expert reasoning, Cura 1T leads the MedXpertQA text split at 60.0 (GPT-5.5 59.6, Opus 4.8 56.2) and ranks second to GPT-5.5 on the multimodal split at 72.2. MedXpertQA asks expert-level exam questions across 17 medical specialties; the multimodal cases pair diverse clinical images with patient records and examination results. On agentic execution, Cura 1T edges Opus 4.8 on AgentClinic, 79.6 vs 79.4, and doubles its base's performance on the NEJM cases (0.400 → 0.800). On MedAgentBench it reaches 94.0 task success, within 3.7 points of the best frontier reference, after three kept rounds of tool-use repair.
Out-of-domain
Specialization usually costs generality; retention-anchor data is the loop's counter. Cura 1T stays in the top five on every out-of-domain leaderboard we track, and it leads outright on AIME 2025 (96.7), τ²-Retail (88.6), and τ²-Telecom (100.0). The healthcare specialization does not erode its general reasoning or agentic capability.
Full benchmark table
| Cura 1T | Claude Opus 4.8 | GPT-5.5 | Gemini 3.1 Pro | Claude Fable 5 | Kimi-K2.6 | |
|---|---|---|---|---|---|---|
| HealthBench Professional | 66.2 | 55.8 | 51.8 | 43.8 | 66.0 | 50.3 |
| HealthBench Hard | 36.8 | 22.2 | 31.5 | 20.6 | — | 22.2 |
| Cura 1T | Claude Opus 4.8 | GPT-5.5 | Kimi-K2.6 | |
|---|---|---|---|---|
| Text | 60.0 | 56.2 | 59.6 | 48.4 |
| Multimodal | 72.2 | 71.0 | 77.1 | 67.2 |
| Cura 1T | Claude Opus 4.8 | GPT-5.5 | Kimi-K2.6 | |
|---|---|---|---|---|
| MedQA | 87.9 | 84.1 | 83.2 | 86.9 |
| MedQA-Ext | 85.0 | 87.4 | 80.8 | 82.7 |
| NEJM | 80.0 | 80.0 | 46.7 | 40.0 |
| NEJM-Ext | 62.5 | 60.8 | 35.8 | 56.7 |
| Overall | 79.6 | 79.4 | 68.4 | 75.4 |
| Cura 1T | Claude Opus 4.8 | GPT-5.5 | Gemini 3.1 Pro | Kimi-K2.6 | |
|---|---|---|---|---|---|
| MedAgentBench | 94.0 | 93.7 | 89.4 | 91.3 | 84.7 |
| Cura 1T | Best other published | ||
|---|---|---|---|
| AIME 2025 | 96.7 | 96.7 | DeepSeek V3.2 |
| AIME 2026 | 93.3 | 98.3† | Gemini 3.1 Pro |
| GPQA-Diamond | 89.9 | 94.1 | Gemini 3.1 Pro |
| τ²-Airline | 76.0 | 84.0 | Claude Opus 4.5 |
| τ²-Retail | 88.6 | 90.8† | Gemini 3.1 Pro |
| τ²-Telecom | 100.0 | 99.3† | Gemini 3.1 Pro |
† Externally reported (vendor announcements / public leaderboards), not run on our harness; protocols may differ. Hover a value for details.
Evaluation notes
- HealthBench Professional / Hard: Physician-authored rubric scores at T=1.0 on the full sets.
- MedXpertQA: Expert-level medical exam QA spanning 17 specialties and 11 body systems; exact-letter pass@1 at T=1.0; the overall score combines 2,450 text and 2,000 multimodal questions.
- AgentClinic: Pass@1 under the tool-native protocol at T=1.0, with simulated patient and measurement agents.
- MedAgentBench: Task success as a native tool-caller against a running FHIR server; the round-by-round development path uses T=0.6.
- Out-of-domain: Pass@1 at T=1.0; each panel shows that leaderboard's top five.
OpenAI-compatible API
Point any OpenAI SDK at inference.actava.ai/v1 and change the model id. Two endpoints: /v1/models and /v1/chat/completions.
curl https://inference.actava.ai/v1/chat/completions \
-H "Authorization: Bearer $ACTAVA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "actava/cura-soar",
"messages": [{"role": "user", "content": "Summarize the escalation criteria for chest pain triage."}]
}'- 01Get a key. API keys are issued by actAVA: join the waitlist and we'll set you up.
- 02Point your SDK. Any OpenAI SDK works: set base_url="https://inference.actava.ai/v1" and model="actava/cura-soar". 256K context, text + vision, function calling.
- 03Read the guides. Streaming, multi-turn chat, vision, tool calls, JSON mode, and prompt caching are covered in the docs.
FAQ
Build healthcare AI with Cura 1T
OpenAI-compatible API, 256K context, text + vision. Keys are issued by actAVA.
Join waitlistCura 1T is a research model, not a medical service, and not a substitute for a clinician. Benchmark scores do not establish safety for unsupervised clinical use.