# Anyone try XeStrata on Intel Arc? > Source: > Published: 2026-10-29 04:41:42+00:00 I’ve been running it for about two weeks on a single B70, and it has become my daily driver My setup is pretty modest with Qwen3.8-Flash-Next (Swift 1.5 IQ3_S). The experts mostly live in system RAM and the B70 holds the hot ones, I compared this to Qwen 3.8 27B and ended up sticking with this The main driver was the performance difference between Strata and XeStrata I had claude create some arbirtrary workloads for a quick comparison and got the following results Absolute numbers for both models through llama-swap, 192k context, INT8 KV, MTP spec 4) Strata vs XeStrata (same GGUF, context, MTP, prefill and reserve, 3 seeds, thinking on) Decode tok/s, upstream Strata v0.1.45 → XeStrata: ┌──────────┬────────┬──────────┐ │ Task │ Strata │ XeStrata │ ├──────────┼────────┼──────────┤ │ bugfix │ 37.7 │ 51.4 │ ├──────────┼────────┼──────────┤ │ code │ 32.7 │ 49.2 │ ├──────────┼────────┼──────────┤ │ invoice │ 31.7 │ 66.2 │ ├──────────┼────────┼──────────┤ │ incident │ 28.7 │ 52.9 │ └──────────┴────────┴──────────┘ Speed was there but should be noted that these are pretty much one shot runs, not an average over a large number of prompts. Answers on the checkable tasks were equally correct. The text was not token-identical Conversation cache This is the feature I like most for agentic use. The engine parks finished conversations’ KV state in RAM I give it 25 GiB, and retain up 16 conversations. When a conversation comes back, it resumes instead of re-prefilling: For agents and coding tools that re-send a long prefix every turn, this matters more than raw decode speed. Things I hit