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English(EN) Benchmark - 4x 5060 Ti (64GB VRAM) (P2P) - Qwen3.6 27B (INT8 /w bf16 kv cache) @ 8 concurrency with SGLang. SGLang seems to handle higher concurrency better with this setup

Qwen3.6-27B 在 4x 5060 Ti GPU 上使用 SGLang 进行基准测试

作者 PulseAugur 编辑部 · [1 个来源] ·

一位Reddit用户分享了在配备四块Nvidia RTX 5060 Ti GPU（总共64GB显存）的设备上运行Qwen3.6-27B模型的基准测试结果。该基准测试使用了SGLang，一个在此特定配置下似乎比VLLM更有效地处理更高并发的框架。用户提供了详细的性能指标，包括吞吐量、延迟和首次响应时间，以及使用的SGLang脚本和基准测试命令。 AI

影响 展示了SGLang在本地LLM部署中实现更高并发的潜力。

排序理由 用户分享的特定模型和框架配置的基准测试。

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Qwen3.6-27B 在 4x 5060 Ti GPU 上使用 SGLang 进行基准测试

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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/joorklee ·

    基准测试 - 4x 5060 Ti (64GB 显存) (P2P) - Qwen3.6 27B (INT8 /w bf16 kv cache) @ 8 并发，使用 SGLang。SGLang 在此设置下似乎能更好地处理更高的并发

    <!-- SC_OFF --><div class="md"><p>I recently posted some posts with VLLM showing issues with TTFT and concurrency with 4x 5060 ti's. Wanted to share this benchmark to provide what worked for me so other people that are planning to go the 4x 5060 ti route aren't discouraged.</p> <…

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