Unverified60% confidenceBenchmarkExact time
In the time-to-first-token test on a 70-billion-parameter model, the M3 Ultra took 31.6 seconds while the M5 Ultra took only 7.7 seconds, achieving approximately 4.1x, close to Apple's claimed 4.3x.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
9/23/2026
First Seen
Valid until: 12/22/2026
Sources
Related Entities
Related Claims
UnverifiedRunning a 27B model on M1 Max with a 32,000-token prompt requires waiting more than 500 seconds before the first character is output, whereas the M5 Max takes less than one minute (approximately 40 seconds with optimized software).78% similarUnverifiedOn a MacBook Pro M5 Pro with 48 GB of memory and a 32K context window, the average time per search question in Markdown (restrictor) mode: Qwen 3.8 27B about 42 seconds, Meta Muse Glimmer 30B about 62 seconds, Prism Bonsai 27B about 24 seconds, and Gemma 4 12B QAT about 16 seconds (about 43 seconds after switching to Markdown Raw).73% similarUnverifiedTesting the same scene and the same sentence 10 times each, DeepSeek's average response time was 3.68 seconds, M3's was 10.70 seconds, and pre-optimization M3.1's was as high as 20.35 seconds.73% similarVerifiedA 3-billion-parameter Llama takes 1 to 3 seconds per call on CPU, while a 70B model takes 40 seconds per call.70% similarVerifiedOn a T4 GPU, Laya takes 33 milliseconds per single question, and batch processing can compress that to 7 milliseconds69% similar
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