Clarke 1.0

For best balance of capability, speed, and cost.

Balanced Performance

Best For:
1

RAG and knowledge assistants

Answer over internal docs, policies, customer dat a, and knowledge bases

2

Enterprise copilots

Assist sales, support, finance, legal, and engineering teams with contextual intelligence

3

Agentic workflows with 
tool use

Call APIs, return structured outputs, execute multi-step business processes

Pricing
input Tokens
$1.50 / MTok
output Tokens
$7.00 / MTok
Pricing

Significant savings with prompt caching (up to 90%) on repeated prompts.

Equivilancy

Comparable to Sonnet 4.6and GPT-5.4

Primary use cases

RAG and knowledge assistants

Answer over internal docs, policies, tickets, customer data, and knowledge bases.

Enterprise copilots

Assist sales, support, finance, legal, engineering, and operations teams.

Agentic workflows

Use tools, call APIs, and execute multi-step business processes.

Code assistance

Generate, debug, refactor, and explain code across production teams.

Structured outputs

Return JSON, classifications, summaries, and workflow-ready responses.

Customer-facing AI

Power AI features inside SaaS, fintech, healthcare, legal, and enterprise apps.

Document reasoning

Analyze contracts, emails, transcripts, filings, manuals, and research.

Key capabilities

1

The model for most production workloads

Clarke is the model to use when Tycho is too lightweight and Hal is more than the task requires. Built for everyday enterprise intelligence: capable enough for complex workflows, efficient enough for production scale.

2

Designed for Claude and OpenAI migration

Clarke gives teams a practical alternative to incumbent flagship endpoints. Developers keep a familiar API pattern. Product teams keep the same user experience. Finance gets a materially better cost structure.

3

Built for agents and tools

Clarke is designed for modern AI applications that do more than chat. Use it to call tools, return structured outputs, reason over retrieved context, and execute multi-step workflows.

4

Enterprise controls without model ops

Clarke gives enterprises the outcome they want from open models without requiring them to select, host, tune, monitor, and maintain the model stack themselves. Radium abstracts the complexity behind a production API.

?

For teams using Sonnet or GPT flagship/default-class models.

Clarke is the Radium model for teams that would otherwise default to Claude Sonnet or a flagship OpenAI endpoint. It is designed to be the first model enterprise teams test when they want to move meaningful production volume away from incumbent API providers without compromising the application experience.

Move your default AI workloads to Clarke.

Clarke is the best starting point for enterprise teams replacing Claude Sonnet or OpenAI flagship usage with Radium.