IFM/K2-Horizon-7B-Uno · Hugging Face - 5200tps with no quality loss

Reddit r/LocalLLaMA Models
large-language-model diffusion-augmented ai-model benchmarking open-source hugging-face efficiency

Summary

The article presents K2-Horizon-7B-Uno, a diffusion-augmented LLM that combines autoregressive and diffusion pathways to achieve 5200 tokens per second throughput without quality loss, with benchmarks showing competitive performance across various tasks.

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Cached at: 09/17/26, 07:47 PM

IFM/K2-Horizon-7B-Uno · Hugging Face

Source: https://huggingface.co/IFM/K2-Horizon-7B-Uno Paper:Unlocking Lossless Speedups in LLMs via Discrete Diffusion Project Page:https://s-sahoo.github.io/uno/ Code:https://github.com/ifm-ai/uno

We presentK2\-Horizon\-7B\-Uno, a diffusion-augmented LLM with two pathways in a unified architecture:

  • The AR pathway uses the AR weights of theK2-Horizon-7Bmodel.
  • The diffusion pathway augments these weights with LoRA-based diffusion adapters.

results_overview

This repository contains the adapter only. The base-model weights are hosted separately inIFM/K2-Horizon-7B.

https://huggingface.co/IFM/K2-Horizon-7B-Uno#codeCode

Selected evaluation scripts are available inscripts/k2_horizon. The full evaluation suite will be released soon.

https://huggingface.co/IFM/K2-Horizon-7B-Uno#evaluation-resultsEvaluation results

The main number is the benchmark score and the subscript is TPF. Bold marks the best score in each row.\-\-andN/Adenote unavailable results.

OursReference modelsBenchmarkUno 8BNemotron-Diff 14BMercury 2 size N/ADiff-Gemma 26B-A4BAgentic Tool Useτ3Banking25.8----9N/A--τ2Telecom90.12.4614.34.871N/A68.118.8τ2Retail67.13.005.63.1--65.523.7Terminal-Bench v2.139.12.654.57.527N/A14.714.1Agentic CodingSWE-bench Verified70.13.080.81.5--18.75.6Long-Context ReasoningAA-LCR68.02.857.31.136N/A19.710.8Science and KnowledgeHumanity’s Last Exam18.62.472.67.216N/A9.214.1GPQA-Diamond77.12.7140.47.677N/A70.711.9AA-Omniscience14.32.2311.011.120N/A17.79.9MathGSM8K95.42.8893.16.1--95.128.9MATH50098.92.8689.25.6--92.424.1AIME-2493.02.9056.74.9--73.716.9AIME-2590.72.9640.04.5--74.318.9AIME-2686.32.8446.74.8--70.717.8CodingMBPP84.12.4473.85.3--80.115.5HumanEval95.22.6684.87.5--95.128.2Efficiency SummaryAverage TPF****2.715.41N/A17.56System Throughput****5,2552,7941,1971,136Per-request Throughput405290769836

https://huggingface.co/IFM/K2-Horizon-7B-Uno#citationCitation

If you find this model useful, please cite:

@misc{k2_horizon_7b_uno,
  title        = {K2-Horizon-7B-Uno},
  author       = {Institute of Foundation Models},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/IFM/K2-Horizon-7B-Uno}},
}

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