Pull requests / #1784
#1784 bench: add RTX 5060 Ti / Xeon E5-2680 v4 community results
closed · @VykosX · 0 comments · View on GitHub
BenchmarksSetup & installNVIDIA / CUDAModels & quantsDocumentationWindows
Description
## Summary Adds a results-only Strata 0.1.41 community benchmark submission for a Windows 10 machine with: - NVIDIA GeForce RTX 5060 Ti 16 GB - Intel Xeon E5-2680 v4, 14 cores / 28 threads - 64 GB RAM - PCIe Gen 3 x8 Two optimized, text-only Qwen3.8-Flash-Next configurations were measured: Coder IQ1_M and an abliterated Q2_0 derivative. No engine, server, or Web UI code is changed by this PR. ## Method The submitted `benchmark.py` is byte-for-byte unchanged from the repository's community benchmark script. For each model: - one warm-up request was excluded - three fresh requests were run serially at 4,096 / 32,768 / 128,000 prompt tokens - every measured request generated exactly 256 tokens - temperature was 0 - reasoning was disabled - every prompt used a unique nonce - Strata reported **zero reused prompt tokens** in all 18 measured requests - loading time was excluded; each model remained loaded for its complete nine-request sweep The compact submission includes results, summaries, initial server status, Strata BUILD metadata, sanitized measured configs, and a README. Bulky raw request/chunk dumps were intentionally omitted and are documented in `TRIMMED.md`. ## Results — Coder IQ1_M Median of three runs: | Prompt tokens | Prompt tok/s | Decode tok/s | TTFT | | ---: | ---: | ---: | ---: | | 4,096 | **1,179.7** | **47.46** | **3.529 s** | | 32,768 | **1,600.6** | **51.02** | **20.558 s** | | 128,000 | **1,859.5** | **49.13** | **69.047 s** | ## Results — abliterated Q2_0 Median of three runs: | Prompt tokens | Prompt tok/s | Decode tok/s | TTFT | | ---: | ---: | ---: | ---: | | 4,096 | **782.2** | **68.02** | **5.273 s** | | 32,768 | **1,549.4** | **73.39** | **21.224 s** | | 128,000 | **1,513.8** | **68.54** | **84.751 s** | ## Notes - Both are optimized local configurations rather than Strata setup defaults. - Both use a 262,144-token context limit, INT8 KV, resident KV, and MTP speculative decoding. - No vision projector was loaded for either accepted run. - The Q2 arm is an abliterated derivative with a workload-trained expert profile; the benchmark reports throughput, not a quality comparison. - The 128K test does not fill the full 262K context window. - The accepted benchmark runs were single-client, serial, and uncontaminated. Full min/max ranges, total timings, exact measured settings, limitations, and hardware/software details are in the submitted `README.md`, `results.json`, and `summary.json`.
Related on strata.com
Editorial links to help you install, pick models, or read release notes — not part of the upstream thread.