# MTIA 300 will be used for ranking and recommendations training, and is already in production.

*semiconductor, genai · news · 2026-03-11 · MarketScreener*

## Key points

- Meta's MTIA 300 chip is already in production for ranking and recommendation model training.
- Future MTIA chips, including 400, 450, and 500, will mainly target GenAI inference workloads.
- Meta's modular MTIA chips can be deployed in existing rack infrastructure for faster implementation.
- Meta plans to release new MTIA chip generations every six months, surpassing industry refresh cycles.
- MTIA 450 and 500 chips are optimized primarily for GenAI inference, rather than pre-training workloads.

Meta Platforms, Inc. announced continuing to advance the MTIA roadmap by developing four new generations of chips, each bringing significant improvements in compute, memory bandwidth, and efficiency. MTIA 300 will be used for ranking and recommendations training, and is already in production. MTIA 400, 450 and 500 will be capable of handling all workloads, but we will primarily use these chips to support GenAI inference production in the near future and into 2027. The modularity of our silicon allows these new chips to drop into existing rack system infrastructure, accelerating time-to-production. Thecompany developed a competitive strategy for MTIA by prioritizing rapid, iterative development, an inference-first focus, and frictionless adoption by building natively on industry standards. While the industry typically launches a new AI chip every one to two years, we?ve developed the capacity to release ours every six months or less by building on our modular, reusable designs. This accelerated pace enables us to quickly adapt to evolving AI techniques, adopt the latest hardware technologies, and minimize costs associated with developing and deploying new chip generations. Mainstream chips are typically built for the most demanding workload ? large-scale GenAI pre-training ? and then applied, often less cost-effectively, to other workloads like GenAI inference. The company take the opposite approach: MTIA 450 and 500 are optimized first for GenAI inference, and they can then be used to support other workloads as needed, including ranking and recommendations training and inference, as well as GenAI training. This keeps MTIA well-tuned to the anticipated growth in GenAI inference demand. MTIA is built on industry-standard software and hardware ecosystems, like PyTorch, vLLM, Triton, and the Open Compute Project (OCP), from the beginning, enabling frictionless adoption of MTIA chips. Beyond industry-standard software, MTIA?s system and rack solutions align with OCP standards, enabling MTIA to be seamlessly deployed in data centers. There is no single chip that can meet all the demands across varying needs, which is why the company is working to deploy a variety of chips that are optimized for each of different workloads. The company believe portfolio approach will enable to advance and innovate at an unmatched pace, bringing us closer to goal of creating personal superintelligence for all.

**Companies:** Meta Platforms, Inc.
**Countries:** United States

[Read the full story on MarketScreener](https://www.marketscreener.com/news/meta-expands-custom-silicon-to-power-ai-workloads-ce7e5fdcd18ef620)

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