ukisai/Swift-Qwen3.8-27B-GGUF
image-text-to-text model by ukisai
Older snapshot: check the original source for current information.
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
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. The prompt is a sample from LiveCodeBench v6 How to reproduce Serving: BF16 · vLLM 0.27.1 · Qwen3 parser · context 262,144 · thinking xhigh. Sampling: temperature 1.0 · topp 0.95 · topk 20 · minp 0 · presencepenalty 0 · repetitionpenalty 1. Benchmarks: averages over five seeds (0–4) per model; five trials per task for Terminal-Bench. BenchmarkOutput cap Quantized deployment is the intended use for Swift: lower-memory weights paired with shorter reasoning. The INT4 evaluations below come from the source model card and were run on W4A16 and AWQ checkpoints, not on this F16 GGUF. They retain token savings across GPQA, IFBench, and AIME. On AIME, Swift matches or improves accuracy and reduces output-cap failures by 31–33%. Quantized evaluation settings…
Read the full model card ↗ · Preview checked 2026-10-27T18:11:29.423Z
Inside the original model card — Document outline
- Swift-Qwen3.8-27B GGUF
- Evaluation scope
- Benchmarks
- Quantized evaluations
- GGUF quantizations
- KV cache
- Training approach
- How to use
- llama.cpp
- Multimodal
- MTP
- Ollama
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the model card
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
Documentation belongs to its respective authors. Reported project/model license: other. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
ukisai/Swift-Qwen3.8-27B-GGUF is a image-text-to-text model repository published by ukisai on Hugging Face. The source reports the gguf library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- gguf
- Recent downloads (30 days)
- 249,636
- Cumulative likes
- 442
- Hugging Face trending score
- 53
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-09-11T14:58:56.000Z
- Last modified
- 2026-09-24T16:17:02.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: ukisai/Swift-Qwen3.8-27b
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.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-01T06:38:22.024Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.