Low-Power AI Silicon
Chip design focused on inference efficiency, stable deployment, and energy-aware execution.
Low-Power Silicon for High-Bandwidth Inference
AI Inference, Mining Intelligence.
High-Bandwidth AI Inference Infrastructure
MarsLab builds low-power AI chips and high-bandwidth inference infrastructure to extract more intelligence from every watt, every byte of memory bandwidth, and every inference cycle.
Technology
Low-Power Silicon for High-Bandwidth Inference
Large-model deployment is moving from peak FLOPS alone toward sustained token production under memory, power, and system constraints.
High-Bandwidth Memory Architecture
A roadmap toward 3D-stacked memory architecture that brings memory closer to logic and reduces data movement cost.
Software-Hardware Co-Design
Runtime, compiler, kernel, memory layout, NoC, and KV cache decisions feed back into hardware architecture.
Architecture
From General-Purpose Acceleration to Inference-Centric Architecture
Traditional high-end GPU systems often rely on 2.5D packaging with HBM beside the compute die. MarsLab is designing toward tighter logic-memory integration for decode-heavy inference workloads.
Traditional GPU Inference Stack
2.5D package, HBM beside compute die, general-purpose software stack, and high memory movement cost in decode-heavy workloads.
MarsLab High-Bandwidth Inference Stack
3D-stacked memory, logic closer to memory, runtime-guided data placement, and KV cache-aware execution.
Roadmap
M100 Today · M200 Next
M100 helps MarsLab enter real deployment constraints today. M200 is the next-generation high-bandwidth inference architecture, designed for workload-dependent gains in decode-heavy scenarios.
M100 Today
For inference deployment and software validation.
- 300 TOPS compute
- 3D-stacked high-bandwidth memory
- High-speed interconnect bandwidth
M200 Next
Next-generation architecture for decode-heavy inference workloads.
- 1P+ compute
- up to 4-die packaging
- 3D-stacked high-bandwidth memory
- HBM expansion memory
- High-speed interconnect bandwidth
- FP4 / FP8 support
Runtime-System-Silicon Feedback Loop
Real workloads → runtime tuning → system deployment → silicon iteration → faster inference.
Careers
Build AI chips and inference systems.
We are hiring across chip architecture, DFT, RTL, physical design, verification, runtime, compiler, and AI infra.
Contact
Contact
For company inquiries and careers, contact the MarsLab HR team.
Email: hr@marslabai.com