ukisai/Swift1.5-Qwen3.8-Flash-Next

image-text-to-text model by ukisai

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Swift 1.5 Qwen3.8-Flash-Next is UkisAI's reasoning-efficient derivative of Qwen3.8-Flash-Next. It uses 63.4% fewer thinking tokens, with a 1.8x speed up while keeping the accuracy loss <1% vs base on xhigh. We gave base Qwen3.8-Flash-Next and Swift 1.5 Qwen3.8-Flash-Next the same prompt: Try the game yourself here: https://ukisai.com/swift-games/flash-next Base Qwen3.8-Flash-Next took 8 minutes 52 seconds to build its game. Swift 1.5 took 4 minutes 56 seconds. We made Swift Flash Next efficient by figuring out which tokens were linked to pathological overthinking and penalizing them without "attacking" the reasoning length directly then regained the accuracy with RL and OPD, leading to "compressed" token usage while maintaining accuracy. Swift 1.5 produces shorter reasoning traces. In our testing, we also observe fewer overthinking errors. This release also features our previously mentioned post-training methods adapted specifically for coding and long-horizon agent work such as personal agents, terminal use and software engineering. Our training data…

ukisai/Swift1.5-Qwen3.8-Flash-Next on Hugging Face A short preview, not the full document.

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  1. Swift 1.5 Qwen3.8-Flash-Next
  2. Demo
  3. Training approach
  4. Evaluation
  5. Efficiency across reasoning efforts
  6. Quantized models
  7. How to use
  8. GGUF download
  9. UkisAI API
  10. vLLM
  11. SGLang
  12. Transformers

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Model overview

ukisai/Swift1.5-Qwen3.8-Flash-Next is a image-text-to-text model repository published by ukisai on Hugging Face. The source reports the transformers library.

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Model facts

Task
image-text-to-text
Library
transformers
Recent downloads (30 days)
445
Cumulative likes
53
Hugging Face trending score
53
Reported safetensors parameters
179,999,981,459
Architecture
Qwen4ExpForConditionalGeneration
License
other
Access
Not gated by Hugging Face
Created
2026-09-22T08:54:04.000Z
Last modified
2026-09-24T16:22:00.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: Qwen/Qwen3.8-Flash-Next

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-09-29T06:38:06.650Z. Daily imports are snapshots, not real-time monitoring.

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