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Qwen3 coder 30b decode speed analyzed on RTX Spark GPU

By PulseAugur Editorial · [1 sources] ·

A technical analysis of the Qwen3 coder 30b model on an RTX Spark GPU reveals that decode speed decreases linearly with context length. The study found that using f16 precision for the cache results in a decode time of approximately 11.8 ms plus 0.39 ms per 1,000 tokens, while q8_0 precision is slower and less efficient. Prompt processing speed also declines significantly with longer contexts, with the GPU operating at lower clock speeds during prompt reading compared to token generation. AI

IMPACT Provides insights into the performance characteristics of LLMs with varying context lengths, relevant for optimizing inference.

RANK_REASON Technical analysis of model performance and speed on specific hardware. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

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

Qwen3 coder 30b decode speed analyzed on RTX Spark GPU

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Technical analysis of model performance and speed on specific hardware. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Steef-Jan Wiggers ·

    Every 1,000 tokens of context costs 0.39 ms: decode speed from 1K to 100K on RTX Spark

    <p>On my Surface Laptop Ultra, qwen3-coder:30b's time per token grows in a straight line with the context it has to read: 11.8 ms plus 0.39 ms for every 1,000 tokens of f16 cache. That's within 7% of what memory bandwidth predicts, so the bytes-per-token model from my <a href="ht…

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