BrainiaK Deploys Pipeline On Jetson Thor T5000
AI-assisted, source-derived brief produced by the Let's Data Science Automated News Desk. The source material used is linked on this page.
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In mid-2025 engineers deployed BrainiaK — a full agentic knowledge pipeline — on NVIDIA's Jetson Thor T5000, running a 122B Qwen3.5 model quantized to AWQ-4bit entirely in 128 GB unified LPDDR5X memory. The stack uses vLLM, Docker Compose, composite memory, tool execution, and MathCore, delivering ~13 tokens/second and up to 32,000-token contexts on a single edge device. This demonstrates reproducible, on-premise agent deployment without cloud inference.
Key Points
- 1Runs Qwen3.5-122B AWQ-4bit entirely in 128GB unified LPDDR5X memory on Jetson Thor T5000
- 2Eliminates CPU-GPU transfer overhead enabling single-device inference and tenant-isolated on-premise data sovereignty
- 3Provides a reproducible, Dockerized agent stack with tools, composite memory, and async request handling
Scoring Rationale
High practical novelty and reproducible guidance, but constrained by specific Jetson Thor hardware and single-source implementation details.
Sources
Public references used for this report.
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