#3389 [Benchmark] 2x RTX 3060 (layer split), Xeon E5-2697 v2 without AVX2, Swift 1.5 IQ2_XS (SC117 abliterated), 0.1.45

说明

## Hardware

- GPU: **2x NVIDIA GeForce RTX 3060, 12 GiB each**, used as a **two-card layer split** (`--layer-split auto`, both cards)
- CPU: **Intel Xeon E5-2697 v2 @ 2.70 GHz** (dual socket, 12 cores each = 24 cores / 48 threads). **No AVX2, no AVX-512** — the engine is the locally compiled "avx"-floor build for older CPUs
- RAM: 127.9 GiB | OS: Windows 11 (10.0.26200) | driver 610.88 | CUDA 13.3
- Strata: project 0.1.45, commit 477ac13c; engine 0.1.45 (source build for this CPU)

## Model and configuration

- **swift-1.5-iq2_xs** — the **SC117 abliterated (uncensored)** Swift 1.5 build of Qwen3.8-Flash-Next, IQ2_XS
- Context 128000, q4_0 KV, MTP draft (`--spec 4`), vision on, parallel 1
- Tuned engine args (unchanged from the install): `--kv-resident 32768`, `--prefill auto:32768`, `--conversation-cache-mib 8192`, `--pipeline-windows 2`, `STRATA_ARENA_PIN_GIB=26`
- Measured with `tools/strata_bench.py` (3 runs per test, medians with ranges); thinking off, temp 0

## Results (median, range)

| Test | Value |
| --- | --- |
| short chat decode | **54.0 tok/s** (46.7–59.9) |
| short chat TTFT | 0.85 s (0.76–0.97) |
| 4K prompt, fresh | **569.9 tok/s** (564.9–579.7), TTFT 7.11 s |
| 16K prompt, fresh | **820.0 tok/s** (814.8–824.1), TTFT 19.65 s |
| agent decode (follow-up turns) | 50.2 tok/s (40.9–63.1) |
| agent conversation-cache hit | 68.8 % |

Full per-turn agent table, prompts and engine log excerpt are in the README this README is pasted from (result folder `bench/results-v045-baseline/2026-10-19-community-rtx-3060-swift-1-5-iq2-xs/`).

## Why this setup matters

- **No AVX2 CPU**: the older-CPU "avx" engine floor still reaches ~54 tok/s decode and ~570/820 tok/s on 4K/16K prompts with a two-card layer split — useful data point for other AVX2-less servers.
- **Abliterated model**: this is the SC117 refusal-reduced (uncensored) Swift 1.5 build, so prompt/decode numbers are for the abliterated weights, not the stock Swift.
- It is the same GPU pair as #2608, but on different CPU/OS/model/engine, so not a duplicate.