How fal.ai Achieved 16x Throughput on Qwen3.6 Using DSpark for Ideogram V4 Prompt Expansion
fal.ai achieved 16x higher throughput and ~1000 tok/s on Qwen3.6 for Ideogram V4's prompt expander feature using DSpark on SGLang. The article explains the technical challenge of needing high interactivity per user for prompt expansion in text-to-image generation, and details the engineering solution involving DSpark (a dynamic speculative decoding approach) to dramatically improve throughput and latency without sacrificing quality.
Key quotes
At @fal , we've achieved 16 times higher throughput on Qwen3.6 for a use-case that required high interactivity per user using DSpark on SGLang.
Text-to-image models like Ideogram V4 can generate stunning, highly detailed images. However they're only as good as the prompt you give them, and most users don't write detailed prompts.
If a given prompt is not detailed enough, it might not look as impressive to the user.
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