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DeepSeek-V4-Flash Performance Issues with DSpark Draft Model Reported

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/LocalLLaMA subreddit is experiencing significantly slower performance with the DeepSeek-V4-Flash model when using the DSpark draft model configuration compared to the Multi Token Prediction (MTP) setup. While the MTP configuration achieves a respectable 30-40 tokens per second, the DSpark configuration drops to a mere 1-2 tokens per second. The user is seeking advice on correctly configuring speculative decoding with llama-server to resolve this bottleneck, providing detailed hardware specifications and command-line arguments for both configurations. AI

IMPACT Identifies potential performance bottlenecks in local LLM inference setups, impacting user experience and efficiency.

RANK_REASON User reporting performance issues with a specific model configuration on a local LLM server.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DeepSeek-V4-Flash Performance Issues with DSpark Draft Model Reported

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User reporting performance issues with a specific model configuration on a local LLM server.
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infra, model release
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High
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Story freshness
48 days old
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Easy_Werewolf7903 ·

    Extremely slow DSpark draft model performance (1-2 t/s) with DeepSeek-V4-Flash on llama-server compared to MTP?

    <!-- SC_OFF --><div class="md"><p>Hey everyone, I could use some advice on setting up speculative decoding correctly with <code>llama-server</code>.</p> <p><strong>My Hardware:</strong></p> <ul> <li><strong>GPUs:</strong> RTX 4090 + RTX 6000 Pro (120GB total VRAM)</li> <li><stron…

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