High-Performance Reasoning Swarm with Mastra AI
Construct a distributed agent system designed to handle complex media analysis tasks. This challenge focuses on high-speed inference and orchestration using Groq Cloud and Modal to scale reasoning tasks. The system utilizes GPT-5.4 Pro for synthesis and Claude Sonnet 4.6.6 for creative content formatting, coordinated entirely within the Mastra AI framework to ensure consistent execution.
What you are building
The core problem, expected build, and operating context for this challenge.
Construct a distributed agent system designed to handle complex media analysis tasks. This challenge focuses on high-speed inference and orchestration using Groq Cloud and Modal to scale reasoning tasks. The system utilizes GPT-5.4 Pro for synthesis and Claude Sonnet 4.6.6 for creative content formatting, coordinated entirely within the Mastra AI framework to ensure consistent execution.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Model Switch
Verify model fallback
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Inference Latency
Average seconds per task • target: 2 • range: 0-10
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Master Mastra AI agent orchestration to manage agent state and workflow transitions
Deploy serverless inference containers on Modal to handle specialized high-compute sub-tasks
Implement model routing to use Groq Cloud for fast-path processing versus GPT-5.4 Pro for deep reasoning
Build a Claude Sonnet 4.6.6 synthesis node for generating high-quality media briefing reports
Create custom tools within Mastra AI to interface with media APIs for real-time analysis
Implement observability hooks to monitor token usage and reasoning depth across the swarm
How this agent runs
Evaluation of swarm throughput and reasoning accuracy
Challenge input
Media transcript
Mastra AI
TypeScript agent framework.
GPT-5
Policy Serving in the agent workflow.
Groq Cloud
Low-latency inference cloud.
Evaluated output
Synthesized report
- Verify model fallback
- Average seconds per task • target: 2 • range: 0-10
- Inference Latency target: 2
- 1 public reference case
- TypeScript execution harness
View technical recipe
Configured tools
- Mastra AI · Required
- GPT-5 · Optional
- Groq Cloud · Optional
- Mastra AI · Required
Evaluation contract
- Model Switch · Weight 1
- Inference Latency · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.
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