iPhone 16 Pro settles 41.5 percent below peak over 20 back-to-back prompts

Four authors at Conscious Engines published a benchmark of Qwen 2.5 1.5B at 4-bit across four edge platforms on March 24, 2026, feeding each device the same 258-token prompt 20 times in a row with a 1-second gap instead of once. On an iPhone 16 Pro the first two runs peak at 40.49 tokens per second, and from run 17 onwards the phone holds a plateau of 23.67 tok/s, which the authors put at 41.5 percent below that peak.

The iPhone passes through the three thermal states iOS reports to an app. Runs 1 and 2 sit in Normal and average 36.83 tok/s, runs 3 to 16 sit in Warm and average 24.96 tok/s, and runs 17 to 20 sit in Hot at 23.67 tok/s with a variation of 1.2 percent. The authors write that the 1-second gap allows no thermal recovery, and they measure 5 percent of battery drained over the 20 runs, which they project to roughly 400 replies of this length per charge.

A Samsung Galaxy S24 Ultra degrades more gently in the same test. Its Adreno 750 GPU boosts to 1,000 MHz on runs 4 and 5 for a peak of 12.21 tok/s, then steps down to a 720 to 770 MHz plateau from run 8 where the authors measure 10.38 tok/s, 15 percent off the peak, with a low of 9.55 tok/s on the final run. They stress that reaching this plateau took deliberate tuning, with the display off, the context capped at 2,048 tokens and MLC-LLM’s prefill chunk cut to 128 tokens, and that earlier unconstrained runs hit an OS-enforced GPU frequency floor.

Neither phone ran the model on its NPU. The paper states that MLX dispatches to the A18 Pro GPU through Metal and does not target Apple’s Neural Engine, and that the S24 Ultra ran through MLC-LLM on the Adreno GPU, leaving the Snapdragon 8 Gen 3’s Hexagon NPU outside the measurement. The one NPU that did run the model, a Hailo-10H module in a Raspberry Pi 5, was also the only part that never throttled, holding 6.914 tok/s across all 20 runs with a variation of 0.04 percent at under 2 W, its CPU at 52.7°C and the NPU at 58.5°C, with attention layers that hailo-ollama does not offload falling back to the Pi’s Cortex-A76 CPU. A user running llama.cpp’s Hexagon NPU backend on a Snapdragon 8 Gen 3 phone reported 12.5 tok/s of generation on Gemma 3 4B and said the phone stayed cool.

A laptop RTX 4050 on battery led on speed at 131.7 tok/s and 34.12 W, its GPU climbing from 55°C to 70°C without throttling. Energy per token comes out at 270.5 mJ for the Hailo module measured across the whole system, 297.3 mJ for the RTX 4050 measured at the GPU, and 143.0 mJ for the S24 Ultra plateau derived from the Android fuel gauge with the display off. The authors state that the three readings differ in scope and call the resemblance suggestive rather than settled, and report no energy figure for the iPhone because iOS exposes no per-component power reading. They tested one model, one prompt and one unit per platform across four different runtimes, and describe the results as characterising hardware and software together rather than hardware on its own.