DeepSeek-V4-Flash-0731: When Low is higher than High

I decided to test a few questions against DeepSeek-V4-Flash-0731. Locally, I was running Unsloth's UD-Q2_K_XL quant. After I saw the surprising shape of the results, I tested against DeepSeek's official API to confirm that I didn't do anything wrong. For anyone using OpenRouter, be aware that there is a significant bug that is breaking reasoning effort modes. I ran into that while trying to validate my local results. DeepSeek-V4-Flash-0731 supports four different effort modes, consisting of no reasoning, low, high, and max. We can also see how those are communicated to the model. As I found out, Low is surprisingly verbose. Averaged across 20 requests per mode, here is how many tokens were used by each mode: Mode Local Q2 total / reasoning / final DeepSeek API total / reasoning / final None 801.7 / 0 / 801.7 948.9 / 0 / 948.9 Low 1,227.5 / 874.4 / 353.2 1,349.2 / 889.6 / 459.7 High 605.8 / 410.5 / 195.4 481.5 / 253.9 / 227.7 Max 1,301.4 / 1,031.8 / 269.6 698.7 / 473.9 / 224.8 I really wish that DeepSeek and Artificial Analysis had posted benchmarks for all of the effort modes, instead of only max. submitted by /u/coder543 [link] [comments]

Related

• DeepSeek-V4-Flash-0731 unsloth gguf on A100
• Ran DS V4-Flash-0731 Locally on 3xMI50 32GB @ ~15 t/s TG
• DeepSeek-V4-Flash-0731 on Bosgame M5 with RTX PRO 6000 Max-Q eGPU
• DeepSeek V4 Flash 0731 IQ2_M benchmark for Dual 3060 and 96GB RAM ≈ 3.5 tok/s.

Source: r/LocalLLaMA | 2026-08-02