Radium Clarke 1.0
Strong performance with the best
balance of speed and cost.
The model most teams should start with. Tycho balances capability, speed, and cost for the AI workloads enterprises actually run every day.
Balanced Performance
Radium's balanced production model for the work most enterprises run every day.
RAG and knowledge assistants
Enterprise copilots
Agentic workflows with tool use
Production-ready model for RAG, copilots, agents, and structured outputs.
Radium's default production model for the enterprise AI workloads most teams run every day, from knowledge assistants to multi-step agents.
Clarke 1.0
Strong performance with the best balance of speed and cost.
Significant savings with prompt caching (up to 90%) on repeated prompts.
Clarke 1.0 is best suited for:
- RAG and knowledge assistants
- Enterprise copilots and workflow automation
- Agentic workflows with tool use
- Code assistance and structured outputs
- Customer-facing AI applications
Comparable to Sonnet 4.6
and GPT-5.4
Where delivery
efficiency becomes
pricing power.
Switch in one line of code and run your existing AI workloads more efficiently without rebuilding your application.
Improve unit economics
at production scale
Radium is used by teams shipping
AI into real-world systems
Square’s R&D team used Radium to prototype early (pre-Gen AI) text-to-video and text-to-speech applications.
EQTY Lab used Radium to train a state-of-the-art climate model that was presented at COP28, the United Nations climate change conference.
Realbotix uses Radium to power low-latency, real-time AI interactions on its humanoid robotics platform. Radium enables responsive inference at the speed required for live human–AI interaction.
A leader in generative AI for law, Alexi used Radium to train domain-specific retrieval models. Alexi’s advanced AI platform generates legal memos, arguments, and answers to general litigation queries.
One line of code to switch.
A different class of performance.
Swap OpenAI for Radium in your API call. That's it.