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DeepSeek-V4 Flash Vision Outpaces Qwen in Coding

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πŸ¦™Read original on Reddit r/LocalLLaMA
#local-inference#quantization#model-comparison#coding-assistantsdeepseek-v4-flash-vision-q8deepseek-v4-flash-visionqwen3.8-flash-nextllamastrixhalo

πŸ’‘Raw speed is not the whole story: this local test found DeepSeek finishing coding tasks twice as fast.

⚑ 30-Second TL;DR

What Changed

DeepSeek-V4-Flash-Vision was about 40% slower in raw token generation at the same quantization level.

Why It Matters

The report suggests that end-to-end task completion and reliability can matter more than raw tokens per second for local coding assistants. Results are anecdotal and hardware-dependent, so practitioners should validate them against their own workloads.

What To Do Next

Run the same coding task with Q8_K_XL builds of DeepSeek-V4-Flash-Vision and Qwen3.8-Flash-Next, measuring completion time, retries, and correctness rather than tok/s alone.

Who should care:Developers & AI Engineers

Key Points

  • β€’DeepSeek-V4-Flash-Vision was about 40% slower in raw token generation at the same quantization level.
  • β€’It completed one task in 12 minutes on medium mode versus Qwen3.8-Flash-Next's 25 minutes.
  • β€’Qwen3.8-Flash-Next reportedly failed a task after nearly three hours in xhigh mode.
  • β€’The comparison used Q8_K_XL quantization on dual StrixHalo 128GB hardware.
  • β€’The author observed that Qwen tends to overinterpret underspecified instructions.
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DeepSeek-V4 Flash Vision Outpaces Qwen in Coding | Reddit r/LocalLLaMA | SetupAI | SetupAI