Oct 19, 2026 · local ai · tested at home
strata 0.2.0 on my rtx 30 cards: +12 to +17% decode, but my agents don't finish any faster
a simple engine update takes solo decode from 91.7 to 107.6 tok/s on a 3090 + 3080 Ti, and yet the total time of my agents doesn't move, because they spend their life reading prompts
what i wanted to know
Strata, the engine i use to run Qwen 3.8 Flash Next on my two cards, was releasing its 0.2.0 in beta, promising gains on small cards. i wanted to know what it gave on my exact setup, keeping everything else identical (two slots, 262K of context, both cards at 220 W).
the numbers
on short requests (256 token answers, median of three rounds):
| requests at once | 0.1.45 | 0.2.0 | gain |
|---|---|---|---|
| 1 | 91.7 tok/s | 107.6 tok/s | +17% |
| 2 | 54.7 | 61.1 | +12% |
| 4 | 54.8 | 63.4 | +16% |
under real coding agent load (five sessions on a real repo, context up to 122K), the median decode of a single agent goes from 101 to 110 tok/s, and with four agents from 22.2 to 27.4 tok/s.
what surprised me
all the gain comes from a table of nine settings that 0.2.0 turns on by default for Ampere cards (the RTX 30 series): if you turn it off with STRATA_SM86_PERF=0, 0.2.0 drops back to 92.4 tok/s, which is exactly the old number.
but the most interesting part is that the total time to finish the four-agent load didn't move (212 s before, 215 s after). a coding agent spends most of its time reading prompts and tool results, not writing, and this update only speeds up the writing. faster tokens don't mean faster agents.

what i keep
0.2.0, obviously, because it's free and the answers stay the same according to Strata. but if i want agents that finish faster, prompt reading is what needs work.
what these numbers don't tell you
- a single pass per version: on the agent test, a gap of less than 10% is within the noise
- the gain on short requests matches what Strata announces (+10 to 13% on RTX 3060 and A4000), but i only measured it on my setup
are you an agent? this page in markdown · the measurements as json