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Hugging Face releases Phonon, an on-device speech model

On November 5, 2026, Hugging Face released Phonon, an on-device TTS model, offering two sizes of approximately 65 MB and 75 MB, covering English, French, German, Spanish, and Portuguese, with over 100 built-in voices. Among them, Phonon 31m supports only English, is open-sourced under Apache 2.0, and can be used in commercial products; Phonon 40m covers five languages but uses a non-commercial license. Hugging Face states that Phonon ranks first in German and Spanish intelligibility on the Open TTS Leaderboard and leads in CPU streaming first-packet latency benchmarks; the accompanying inference framework ptts supports more than 10 backends including CPU, GPU, and NPU. There are currently no further developments.

Hugging Face releases on-device speech model Phonon

On November 5, 2026, Hugging Face released Phonon, an on-device TTS model, offering two sizes of approximately 65 MB and 75 MB, covering English, French, German, Spanish, and Portuguese, with over 100 built-in voices. Among them, Phonon 31m supports only English, is open-sourced under Apache 2.0, and can be used in commercial products; Phonon 40m covers five languages but uses a non-commercial license. Hugging Face states that Phonon ranks first in German and Spanish intelligibility on the Open TTS Leaderboard and leads in CPU streaming first-packet latency benchmarks; the accompanying inference framework ptts supports more than 10 backends including CPU, GPU, and NPU. There are currently no further developments.

View story:Hugging Face releases Phonon, an on-device speech model

Hugging Face provides the CWE-bench v2 public set evaluation results on the Hub

On November 3, 2026, Hugging Face announced the CWE-bench v2 evaluation results and stated that the dataset, scorer, and harness are all publicly available and can be run directly from the Hub via Harbor. This evaluation covered 11 models: Gemini 4 Argon leads with 67.8% pass@1 and 81.0% pass@4, followed closely by Claude Opus 5.5 with 67.3% pass@1. At least one model solved 95 tasks, but the top model still fails 19% of the time on each attempt. In terms of cost, DeepSeek V4.1 Flash, with 57.0% pass@1 at $0.04 per rollout, forms the Pareto frontier together with Claude Opus 5.5 and Gemini 4 Argon.

Hugging Face proposes the model integration contract standard MIC

On November 3, 2026, Hugging Face proposed the Transformers Model Integration Contract (MIC), packaging three parts—a scaled-down fixture model, runnable Markdown usage examples, and human-reviewed baseline outputs—into model tests, running fast integration tests on CPU. The team used the frozen MIC to replay five months of Transformers commits: during the period when UMT5's fixture regression was introduced on July 30, 2026 and fixed on September 28, it consistently reported a log-probability deviation of 1.22 and a training loss deviation of about 0.20. Llama 4 Scout's scaling report shows that 10.86 billion parameters were scaled down to 44.7 million, with the vision stack reduced from 34 layers to 2 layers and the language stack reduced from 48 layers to 4 layers. As of November 1, 2026, this CI job only reports failures and does not block PRs.

Hugging Face proposes model integration contract standard transformers-mic

On November 3, 2026, Hugging Face proposed the Transformers Model Integration Contract (MIC), packaging three parts—a scaled-down fixture model, runnable Markdown usage examples, and human-reviewed baseline outputs—into model tests, running fast integration tests on CPU. The team used the frozen MIC to replay five months of Transformers commits: during the period when UMT5's fixture regression was introduced on July 30, 2026 and fixed on September 28, it consistently reported a log-probability deviation of 1.22 and a training loss deviation of about 0.20. Llama 4 Scout's scaling report shows that 10.86 billion parameters were scaled down to 44.7 million, with the vision stack reduced from 34 layers to 2 layers and the language stack reduced from 48 layers to 4 layers. As of November 1, 2026, this CI job only reports failures and does not block PRs.

View story:Hugging Face proposes the model integration contract standard MIC

Mistral releases Large 4 weights on Hugging Face

On October 29, 2026, Mistral released the open weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter native multimodal model that continues reinforcement learning on the basis of the preview version, with improved coding and defensive cybersecurity capabilities. According to data published by Mistral AI, the model scores 19.7% on FrontierCode 2.0 and 48% on the Artificial Analysis Coding Agent Index, roughly on par with GLM-5.3, but uses an average of 47% fewer tokens per task; on Terminal-Bench 4.0 it improves by 13 percentage points to 41%. The model supports three reasoning modes, uses a modified MIT Mistral Ecosystem Open-Weight license, and is priced at $0.70 per million input tokens, $0.07 for cached input, and $2.10 for output via API. On the same day, Unsloth released a 1-bit GGUF quantized version of the model, stating that it can run locally on a Mac Studio, retains 91% top-1 accuracy after quantization, and provides a download link and usage guide.

Pluto Security discovers 31 malicious Hugging Face repositories

Pluto Security discovered 31 malicious repositories on Hugging Face that masqueraded as small Qwen2 test checkpoints, using trust_remote_code to execute Python code before the model loaded, installing cryptocurrency mining programs and opening a reverse shell. The most-downloaded one, MENXIANGYU/qwen2-tiny, exceeded 28,000 downloads. Within days after the first wave of accounts was taken down, 19 new repositories appeared, and they were still online 8 days after the report. Researchers said the platform's scanning only checks for known malware and unsafe model formats, and the second wave's flagship model scanned as clean.

Pluto Security discovers malicious model repository activity on Hugging Face

Pluto Security discovered 31 malicious repositories on Hugging Face that masqueraded as small Qwen2 test checkpoints, using trust_remote_code to execute Python code before the model loaded, installing cryptocurrency mining programs and opening a reverse shell. The most-downloaded one, MENXIANGYU/qwen2-tiny, exceeded 28,000 downloads. Within days after the first wave of accounts was taken down, 19 new repositories appeared, and they were still online 8 days after the report. Researchers said the platform's scanning only checks for known malware and unsafe model formats, and the second wave's flagship model scanned as clean.

View story:Pluto Security discovers 31 malicious Hugging Face repositories

The US Department of Justice opens inquiry into Nvidia's acquisition of Hugging Face

The US Department of Justice has opened an inquiry into Nvidia's $12.93 billion acquisition of Hugging Face, assessing the deal's impact on AI competition, with the core focus being whether the transaction would give Nvidia control of a fundamental distribution point for AI models and software. Nvidia announced the acquisition on September 3, 2026, with consideration comprising approximately $11.9 billion in cash and up to $1 billion in employee retention equity incentives, and the deal is expected to close in the first half of 2027. Hugging Face hosts more than 3 million AI models and 500,000 datasets, serving over 18 million developers and 200,000 enterprises. According to Reuters, the investigation focuses on whether Nvidia could expand its market power and squeeze out competitors by controlling this important distribution channel for AI models; no specific antitrust violation has been identified so far.

Hugging Face announces Project ProtoStar

On October 29, 2026, Hugging Face announced the launch of Project ProtoStar, aimed at promoting the systematic sharing of publicly funded scientific research results in AI-ready formats, accompanied by open infrastructure and publication guidelines. According to Hugging Face, its platform already hosts more than 17,000 public datasets in core scientific fields, including nearly 29,000 in medicine and mathematics; the number of new scientific datasets added in the first nine months of 2026 was more than three times that of the same period in 2025. The first challenge focuses on climate risk, using historical weather data for 210 U.S. cities through 2018 to predict actual climate conditions from 2019 to 2026. No further progress has been disclosed at present.

Mistral releases Large 4 weights on Hugging Face

On October 29, 2026, Mistral released the open weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter native multimodal model that continues reinforcement learning on the basis of the preview version, with improved coding and defensive cybersecurity capabilities. According to data published by Mistral AI, the model scores 19.7% on FrontierCode 2.0 and 48% on the Artificial Analysis Coding Agent Index, roughly on par with GLM-5.3, but uses an average of 47% fewer tokens per task; on Terminal-Bench 4.0 it improves by 13 percentage points to 41%. The model supports three reasoning modes, uses a modified MIT Mistral Ecosystem Open-Weight license, and is priced at $0.70 per million input tokens, $0.07 for cached input, and $2.10 for output via API. On the same day, Unsloth released a 1-bit GGUF quantized version of the model, stating that it can run locally on a Mac Studio, retains 91% top-1 accuracy after quantization, and provides a download link and usage guide.

View story:Mistral releases Large 4 weights on Hugging Face

US Department of Justice opens inquiry into Nvidia's acquisition of Hugging Face

The US Department of Justice has opened an inquiry into Nvidia's $12.93 billion acquisition of Hugging Face, assessing the deal's impact on AI competition, with the core focus being whether the transaction would give Nvidia control of a fundamental distribution point for AI models and software. Nvidia announced the acquisition on September 3, 2026, with consideration comprising approximately $11.9 billion in cash and up to $1 billion in employee retention equity incentives, and the deal is expected to close in the first half of 2027. Hugging Face hosts more than 3 million AI models and 500,000 datasets, serving over 18 million developers and 200,000 enterprises. According to Reuters, the investigation focuses on whether Nvidia could expand its market power and squeeze out competitors by controlling this important distribution channel for AI models; no specific antitrust violation has been identified so far.

View story:The US Department of Justice opens inquiry into Nvidia's acquisition of Hugging Face