Interactive responsiveness · five prompts per service

Short-prompt service responsiveness

A practical service-latency branch: matched short user prompts across the resident TestBench Qwen service, Z13 Qwen, and hosted GPT-6 Luna.

Warm median completion was 0.891 s on TestBench, 2.345 s on Z13, and 2.080 s on Luna. These are descriptive service observations, not a hardware-only comparison or general speed ranking.

Five matched short prompts

Each service received the same five prompt byte strings in sequence, with a 128-token output cap. Temperature was omitted; Qwen used think:false. No answers were quality-graded.

Service / observed setupnTTFT medianTTFT p95*Completion medianCompletion p95*Output tokens median
TestBench system Ollama / Qwen3.6 35B (resident across two RTX 3090s)50.169 s0.176 s0.891 s0.973 s77
Z13 Radeon 8050S / Qwen3.6 35B51.111 s1.118 s2.345 s2.482 s79
Hosted GPT-6 Luna51.478 s1.840 s2.080 s2.648 s81

* Nearest-rank p95 with n=5; descriptive only. Output token counts differ by service and tokenizer.

What the timings include

The Z13 model was not resident at the start; its 7.14 s load occurred during the excluded warm-up. The measured requests followed that warm-up. TestBench's pre-existing model remained resident. Thus these are service-level warm observations under their recorded conditions, not a cold-start comparison.

Interpretation boundary

Local Ollama timings were measured on each model host. Luna timing was measured from the desktop and includes Pi SDK work from before streamSimple through completion; it is not provider-side TTFT, prefill, or decode. Luna's observed payload callback is not wire-confirmed, and the Pi Codex builder may supply its default assistant instruction.

This branch answers how quickly these services returned visible text for this small prompt set. It does not measure answer quality, isolate hardware as the cause, or predict long-context behavior. In particular, the earlier 31k-token Z13 stress prompt is not a proxy for this workload.