Google’s reported move to involve MediaTek in some future data-center AI chips was described in March 2025 as an effort to develop next-generation Tensor Processing Units (TPUs), not as a wholesale replacement of Broadcom. The report pointed to potential cost savings and MediaTek’s relationship with TSMC, but Google has not publicly confirmed the reported arrangement or MediaTek’s exact role. By August 2026, Google’s public roadmap lists Ironwood as generally available and TPU 8t and TPU 8i as coming soon—so the old report should be read as a supply-chain signal, not a confirmed description of those products.
What the MediaTek report said—and what it did not
On March 18, 2025, Android Headlines reported that Google planned to work with Taiwan’s MediaTek on some next-generation AI server chips, citing reporting by The Information. Reuters also reported on the story on March 17, 2025, as indexed by Techmeme. The claim was that MediaTek would help with Google’s TPU program; the available reporting did not establish the final design, production status, or division of work among suppliers. (Android Headlines; Reuters; Techmeme)
The reported target was server infrastructure, not the Tensor-branded processors used in Pixel phones. Most importantly, the original coverage said Google would continue working with Broadcom. “Google taps MediaTek” therefore does not mean “Google replaces Broadcom.”
As of August 2026, Google’s public TPU page does not identify MediaTek as the supplier of any named TPU generation. It lists Ironwood as generally available and TPU 8t and TPU 8i as coming soon. The 2025 report’s forecast for a next-generation chip around 2026 is historical, and it cannot be mapped automatically onto these later public product names. (Google Cloud TPU)
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What Google TPUs are
Tensor Processing Units are Google-designed accelerators for machine-learning work, including model training and inference. Google offers access primarily as cloud capacity rather than as retail accelerator cards for consumers. That gives Google a way to build hardware, software, and cloud services around its own workloads and customer platform. Google’s TPU documentation describes its cloud products and software environment, including JAX, PyTorch/TorchTPU, OpenXLA, MaxText, Tunix, and vLLM. (Google Cloud TPU; TPU documentation)
These server TPUs are distinct from Pixel Tensor processors. A reported MediaTek role in data-center accelerators says nothing by itself about who designs or manufactures phone processors.
Why Google might work with MediaTek
Potentially lower costs
The 2025 coverage said MediaTek could offer a lower chip cost than Broadcom and cited an estimate that Google spent $6 billion to $9 billion on TPUs in 2024. Those are reported claims, not figures independently confirmed by Google. Even if a chip is cheaper to buy, that does not prove a lower cost per trained model or generated token: utilization, energy, networking, memory, software porting, and cloud pricing all affect the economics. (Android Headlines)
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Foundry and supply-chain access
The report presented MediaTek’s relationship with TSMC as a potential advantage. Advanced accelerators need more than a chip design: they depend on access to wafer capacity, high-bandwidth memory, advanced packaging, and coordination across suppliers. A relationship with TSMC could help with execution, but the report does not show that MediaTek controls TSMC capacity for Google or guarantees a production slot.
Supplier diversification
Working with more than one design partner could give Google additional negotiating leverage and reduce reliance on a single external partner. That is a reasonable strategic inference from the reported addition of MediaTek alongside continued Broadcom involvement—not a confirmed statement of Google’s rationale or a guarantee that work will be split evenly.
Why MediaTek’s role and Broadcom’s status remain unclear
A complex accelerator platform can involve separate work in architecture, physical implementation, memory interfaces, interconnect, chiplets and I/O, packaging, validation, and production ramp. Saying that a company is “involved” does not tell readers which of these jobs it performs. The available reporting does not specify whether MediaTek would design a complete TPU, contribute a component, coordinate manufacturing, or take another role.
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- ✅Supports TensorFlow, TensorFlow Lite, ONNX, Keras, Pytorch frameworks
- ✅Supports Linux and Windows. Supports the temperature range of -40°C to 85°C
The reported continuation of Broadcom’s work argues against describing the deal as a confirmed replacement. Google could use different partners for different generations or subsystems; however, the available sources do not establish that division of labor. Without a specific confirmation from Google, MediaTek, Broadcom, or a high-confidence report detailing responsibilities, claims that Broadcom has been displaced go beyond the evidence.
Google’s public TPU roadmap as of August 2026
| Platform | Google’s public status and positioning |
| Trillium | Sixth-generation TPU; generally available. |
| Ironwood | Seventh-generation TPU; generally available. Google lists 9,216 liquid-cooled chips per pod, 42.5 exaFLOPS, and four times the per-chip performance of Trillium. These are Google product-page specifications and claims, not independent benchmark results. |
| TPU 8t | Listed as coming soon for large-scale training. Google says a superpod can contain up to 9,600 chips and claims nearly three times the compute performance per pod over the previous generation. |
| TPU 8i | Listed as coming soon for inference and reinforcement learning. Google claims an 80% performance-per-dollar improvement over previous generations for low-latency inference on large mixture-of-experts models. |
All status and performance figures in this table come from Google’s current TPU page. The performance comparisons are vendor claims, not neutral, independently reproduced tests. The page does not identify MediaTek as the designer or supplier of these platforms. (Google Cloud TPU)
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Rank #4
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How this could challenge NVIDIA
Infrastructure economics
If Google can build and operate suitable TPUs at a lower total cost, it could reduce how many workloads require NVIDIA accelerators in Google’s own infrastructure. It may also have more room to price cloud AI capacity competitively. That outcome depends on real workload economics, not simply the purchase price of a chip.
Cloud differentiation and supply planning
Google Cloud can offer customers access to its own accelerator and integrated software stack, rather than competing only on access to NVIDIA hardware also available from other providers. Custom silicon can also give Google more control over capacity planning and its hardware roadmap when accelerator supply is constrained.
Specialized workloads, not universal superiority
Google does not need a TPU to outperform every NVIDIA GPU on every task. It can optimize hardware for workloads important to Google and its cloud customers, including training, inference, and reinforcement learning. Google’s separate training-focused TPU 8t and inference-focused TPU 8i illustrate this specialization in its public roadmap.
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The challenge is strongest where workloads fit Google’s cloud and software environment. It is less direct for organizations tied to CUDA-specific code, custom NVIDIA kernels, or broad third-party software compatibility. NVIDIA competes through a software ecosystem as well as silicon, so a comparison based on peak compute alone would miss a major part of the decision.
What the report does not prove
- It does not confirm that MediaTek has replaced Broadcom.
- It does not establish MediaTek’s precise design, manufacturing, or packaging responsibilities.
- It does not show that Google will sell the reported chip as a standalone product; Google’s public TPU offering is cloud capacity.
- It does not prove that a Google TPU is faster or cheaper than an NVIDIA system on a given customer workload.
- It does not show that NVIDIA’s wider market position is about to change. The more immediate strategic pressure would be in Google’s own infrastructure and workloads suited to Google Cloud.
- It does not confirm rumored code names or specifications for future TPU generations.
What would show whether the partnership matters
The useful evidence is not just whether MediaTek’s name appears in a headline, but whether the arrangement produces a working, available platform. Watch for:
Quick Recap
- A Google product announcement that identifies the TPU generation and the platform’s availability.
- Specific confirmation from Google, MediaTek, or Broadcom about supplier responsibilities.
- Evidence that wafer capacity, HBM, and advanced packaging can support the planned production volume.
- Cloud availability, regional access, and pricing that let customers compare the platform with alternatives.
- Software support and migration requirements for JAX, PyTorch, OpenXLA, and serving frameworks such as vLLM.
- Independent, workload-specific results that account for utilization, energy, networking, and engineering effort—not only peak chip specifications.
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