Deepseek V4.1-1017本地实测吞吐波动明显
一名 Reddit 用户在 AMD Ryzen 3950X、96GB DDR4 内存、Radeon RX 7900 XTX、Radeon Pro W6800 和 PCIe Gen 3 NVMe 硬盘组成的系统上测试 Deepseek V4.1-1017。测试采用以 IQ2 权重和 Q6 n-gram 为主的约 350GB 模型，峰值达到每秒 19 个 token，通常约为 13 个，有时降至 3 个，预填充速度约为每秒 150 个 token。测试者称波动主要与 I/O 需求有关，长提示词末尾的平均解码速度为每秒 9 个 token。
该报告记录了 Deepseek V4.1-1017 在 Radeon 多显卡与 DDR4 内存组合上的具体运行表现，可为评估超大模型的本地部署条件提供实测参考。
Just a spec to performance report. Tried Maya today on the following:
- 3950x
- 96GB dual channel DDR4 at 3000mhz
- Rx 7900xtx 24GB + w6800 32GB (56GB together)
- pcie gen3 nvme drive
The Deepseek weights used were the mostly iq2 weights with Q6 ngrams. ~350GB on disk. Dspark left on.
I ended up getting wildly varying performance - less due to dspark hits and more due to when I/O was needed.
I got peaks as high as 19t/s, usually hovering around 13t/s, then dropping down to 3t/s for a few seconds, then right back up. Average at the end of a long prompt was 9t/s decode. Prefill is ~150 t/s. . Some prompts it rips through at 15 tokens a second, others it will crawl through at 3-5 tokens per second even if it's the same topic. Its very odd and I've been trying quite a few settings to figure it out.
The model itself is crazy smart - better than the iq4-xs quant of Qwen3.8-Flash-Next I've been running for certain - but it likes to think A LOT and with the already slow average of 9t/s decode I won't be using it for much outside of chatting even if it is the new best model on my machine.
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#Deepseek V4.1-1017#AMD Ryzen 9 3950X#Radeon RX 7900 XTX#Radeon Pro W6800#Qwen3.8-Flash-Next