Dev tools · September 16, 2026
Swift-Qwen3.8-27B, -58.3% thinking, x1.95 speed, accuracy of xhigh
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Swift-Qwen3.8-27B, -58.3% thinking, x1.95 speed, accuracy of xhigh launched on September 16, 2026 with 32 votes, #723 of 8,094 launches that month and more than 95% of that year's launches.
In plain words
Swift-Qwen3.8-27B is an open-source AI reasoning model developed by UkisAI that optimizes the Qwen3.8-27B model for efficiency. It reduces thinking token usage by 58.3% while maintaining near-identical accuracy, achieving 1.95x faster performance on several tasks. The model works by identifying and penalizing reasoning-marker tokens that trigger overthinking during inference, resulting in shorter reasoning traces and fewer errors. It is designed for developers working with large language models who need faster inference without sacrificing performance.
written from the facts on this page · September 2026
From the sources
Swift-Qwen3.8-27B is UkisAI's reasoning-efficient derivative of Qwen3.8-27B, using 58.3% fewer thinking tokens while maintaining near-identical performance ( <1% loss ) and as a result getting a x1.95 speed-up on several tasks. We built Swift by identifying reasoning-marker tokens that, in our analysis, trigger overthinking in Qwen’s reasoning rollouts. We then fine-tuned Qwen by penalizing usage of those tokens while it reasons. Swift produces shorter reasoning traces. In our testing, we also observe fewer overthinking errors. For maximum gains, Swift also includes a transfer component derived from BottleCap AI's ThinkingCap-Qwen3.6-27B . All results below compare the Qwen3.8-27B BF16 base…from huggingface.co
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Qwen3.5 SmallMar 2026 · huggingface.co · ▲3550.8B-9B native multimodal w/ more intelligence, less compute
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