Performance gaps exposed in real-world testing
Tensor G6 can't keep up. Is Google's custom silicon strategy failing?
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Google Adds Pixel 9 Series to Certified Refurbished StoreGoogle's Pixel 11, launched in September 2026, features the Tensor G6 chip, which struggles to match the performance of competing flagship processors from Qualcomm, Apple, and MediaTek. Independent benchmarks reveal significant gaps in CPU and GPU capabilities, raising questions about Google's ability to compete through custom silicon. The Tensor G6 lags behind in sustained workloads, gaming performance, and power efficiency compared to its rivals.
Can Google close the gap with future Tensor chips?
Despite Google's efforts to optimize the Tensor G6 for AI-driven features like real-time translation and computational photography, raw performance remains a weakness. The chip uses a modified ARM architecture with older CPU cores and a less powerful GPU than the Snapdragon 8 Gen 3 or Apple's A18 Pro. This limits the Pixel 11's ability to handle demanding applications and multitasking scenarios effectively.
Benchmark tests show the Tensor G6 scoring up to 30% lower than the Snapdragon 8 Gen 3 in multi-core CPU tasks and nearly 40% behind in GPU-intensive gaming scenarios. Thermal throttling occurs more frequently during extended use, affecting user experience. Google's focus on AI acceleration does not compensate for deficiencies in general-purpose computing, where most smartphone tasks still rely on traditional CPU and GPU performance.
The company faces a critical decision: continue investing in custom silicon despite performance shortcomings or adopt off-the-shelf solutions for better competitiveness. Pixel sales have remained steady due to software strengths, but hardware limitations may hinder long-term growth. Future Tensor iterations must address core performance issues to avoid falling further behind industry leaders.
Frequently Asked Questions
Why does the Tensor G6 underperform compared to rivals? The Tensor G6 uses older CPU cores and a less advanced GPU architecture than competing chips, resulting in lower raw performance despite AI optimizations.
Is Google likely to abandon its custom Tensor chip strategy? There is no indication Google will abandon Tensor, but future versions must improve CPU and GPU performance to remain competitive in the flagship market.
