Meta’s MTIA Custom Silicon: Breaking NVIDIA Dependency

Meta is accelerating development of MTIA (Meta Training and Inference Accelerator), now in its third generation, as part of a multi-year strategy to reduce dependency on NVIDIA GPUs.

The NVIDIA Problem

NVIDIA controls ~80% of the AI chip market. Every major AI company — Meta, Google, Microsoft, Amazon, OpenAI, xAI, Anthropic — depends on the same constrained supply.

Meta’s Silicon Strategy

MTIA (3rd Generation)

  • Custom inference silicon
  • Optimized for Meta’s specific workloads
  • Better performance/watt for recommendations
  • Multiple generations now in production

Rivos Acquisition (~$1B)

  • RISC-V expertise (open architecture)
  • ~80 chip engineers added
  • Path beyond x86/ARM licensing

The Phased Approach

Phase Training Inference
Now NVIDIA GPUs MTIA + NVIDIA
2025-2027 NVIDIA GPUs Mostly MTIA
2028+ Custom + NVIDIA Full MTIA

Strategic Logic

Meta doesn’t need to beat NVIDIA. It needs optionality. Custom silicon for inference reduces dependency enough to negotiate from strength — and ensures survival regardless of GPU allocation politics.


For a deeper strategic analysis, read The Re-Engineering of Meta on The Business Engineer.

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