Image-Text-to-Text
NInfer
qwen3.8
flash-next
nvfp4
fp8
int4
mixed-precision
blackwell
rtx-pro-6000
windows
single-gpu
multimodal
speculative-decoding
Instructions to use jmgao/Swift1.5-Flash-Next-mixed-NInfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NInfer
How to use jmgao/Swift1.5-Flash-Next-mixed-NInfer with NInfer:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Swift 1.5 Qwen3.8-Flash-Next mixed quantization for NInfer
A quantization of ukisai/Swift1.5-Qwen3.8-Flash-Next using primitive-ai/Qwen3.8-Flash-Next-mixed-NVFP4-FP8's methodology to run on igorls's NInfer workstation fork on a single RTX Pro 6000.
The quantized PLE tables in Swift1.5 are identical to the base model, so we take ours from primitive-ai/Qwen3.8-Flash-Next-PLE-quant.
This slightly differs from igorls/Qwen3.8-Flash-Next-mixed-NInfer in that the MTP expert banks are stored in NVFP4 directly instead of BF16 and quantized at runtime.
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Model tree for jmgao/Swift1.5-Flash-Next-mixed-NInfer
Base model
Qwen/Qwen3.8-Flash-Next