Ironwood is Google’s newest AI accelerator chip

Tech Crunch - Apr 9th, 2025
Open on Tech Crunch

During its Cloud Next conference, Google introduced Ironwood, its seventh-generation TPU AI accelerator chip, specifically optimized for inference tasks. Set for release later this year to Google Cloud customers, Ironwood will be available in two configurations: a 256-chip cluster and a 9,216-chip cluster. Google Cloud VP Amin Vahdat highlighted Ironwood’s capabilities, emphasizing its power and energy efficiency, designed to handle inferential AI models at scale. With computing power reaching 4,614 TFLOPs, each Ironwood chip boasts 192GB of RAM and enhanced data processing capabilities, particularly suited for recommendation algorithms. Google plans to integrate Ironwood with its AI Hypercomputer for enhanced computational performance.

Ironwood's launch positions Google in the competitive AI accelerator market, where Nvidia currently dominates, and tech giants like Amazon and Microsoft are also advancing with their own technology. Amazon offers its Trainium, Inferentia, and Graviton processors, while Microsoft supports its Cobalt 100 AI chip through Azure. Ironwood's architecture, designed to reduce data movement and latency, represents a significant breakthrough in AI inference technology. This development signals a robust push by Google to solidify its standing in the AI sector, promising substantial improvements in computation power, memory, and networking for AI applications.

Story submitted by Fairstory

RATING

7.0
Fair Story
Consider it well-founded

The article provides a timely and informative overview of Google's new Ironwood AI accelerator chip, highlighting its technical specifications and potential impact on the AI hardware market. It effectively communicates complex information in a clear and accessible manner, making it suitable for readers with varying levels of technical expertise. However, the story could benefit from greater transparency and independent verification of performance claims to enhance its credibility. While the article offers a balanced perspective by acknowledging the competitive landscape, it lacks in-depth analysis of Ironwood's implications for broader societal and ethical issues related to AI technology. Overall, the article serves as a solid introduction to Ironwood's capabilities but could be strengthened by incorporating more diverse viewpoints and exploring the broader context of AI advancements.

RATING DETAILS

8
Accuracy

The story about Google's Ironwood AI accelerator chip is generally accurate, with specific claims about the chip's capabilities and configurations that align with known information. For instance, the story correctly identifies Ironwood as Google's seventh-generation TPU and notes its optimization for inference. However, some claims, such as those regarding the chip's performance metrics (4,614 TFLOPs and 7.4 Tbps bandwidth), should be independently verified through external benchmarks to ensure precision. Additionally, the story mentions Google's internal benchmarking, which may not be as reliable as third-party evaluations. The article accurately depicts the competitive landscape, mentioning Nvidia, Amazon, and Microsoft as key players, which is consistent with industry reports.

7
Balance

The article provides a fairly balanced view by highlighting Google's advancements with Ironwood while acknowledging the competitive environment in the AI accelerator market. It mentions competitors like Nvidia, Amazon, and Microsoft, which helps present a broader industry context. However, the story primarily focuses on Google's achievements, potentially overshadowing the competitive analysis. The article could benefit from more detailed comparisons of Ironwood's features against those of its competitors to provide a more balanced perspective.

8
Clarity

The article is well-structured and uses clear language to explain complex technical concepts, such as AI inference and TPU configurations. The logical flow of information makes it accessible to readers with varying levels of familiarity with AI technology. However, the article could benefit from additional context or definitions for terms like 'SparseCore' for readers who may not be familiar with technical jargon. Overall, the story maintains a neutral tone and effectively communicates the main points.

6
Source quality

The story relies on Google's statements and a blog post by Google Cloud VP Amin Vahdat, which are authoritative sources regarding Google's technology. However, the reliance on internal sources without external validation or independent expert opinions limits the depth of analysis. The absence of third-party expert commentary or industry analysis reduces the overall credibility, as it lacks diverse viewpoints that could provide a more nuanced understanding of Ironwood's capabilities.

6
Transparency

The article provides clear information about Ironwood's specifications and Google's plans for integration with its AI Hypercomputer. However, it lacks transparency regarding the basis for some claims, such as performance metrics and energy efficiency, which are based on Google's internal assessments. The story does not disclose any potential conflicts of interest or limitations in the data presented, which could affect the reader's understanding of the impartiality of the claims.

Sources

  1. https://www.crn.com/news/cloud/2025/google-cloud-next-the-10-biggest-google-product-launches
  2. https://www.techtarget.com/searchdatacenter/news/366622260/Google-Cloud-Platform-adds-WAN-and-on-premises-AI-services
  3. https://blog.google/technology/ai/google-ai-updates-march-2025/
  4. https://techcrunch.com/2025/04/07/google-is-allegedly-paying-some-ai-staff-to-do-nothing-for-a-year-rather-than-join-rivals/
  5. https://www.techmeme.com/250409/p22