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Google has released the large language model Gemini 4 Carbon and the world model Genie 4; the former surpasses its own Gemini 4 Argon and OpenAI's GPT-6 Astra on comprehensive capability benchmarks. Gemini 4 Carbon focuses on vulnerability detection and patching and is currently available only to select cybersecurity experts; Genie 4 adds audio capabilities, allowing developers to add background sound and dialogue to AI worlds, and a waitlist is now open.
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Diffusion Intelligence releases the diffusion language model Clover-35B-A3B-Preview, which uses a MoE architecture with 35 billion total parameters and about 3 billion activated per token, and supports a thinking mode. On the 49 tasks of the web Agent benchmark WindTunnel, its median execution time was 1.52 seconds, lower than the 3.21 seconds of the Jev + Mercury 2.5 combination, with success rates of 98.6% and 95.9% respectively. On code benchmarks, it scored 73.6 on SWE-bench Verified and 51.7 on Terminal-Bench 2.1, and the team said it will subsequently launch a multimodal version and advance on-device adaptation.
Diffusion Intelligence releases the diffusion language model Clover-35B-A3B-Preview, which uses a MoE architecture with 35 billion total parameters and about 3 billion activated per token, and supports a thinking mode. On the 49 tasks of the web Agent benchmark WindTunnel, its median execution time was 1.52 seconds, lower than the 3.21 seconds of the Jev + Mercury 2.5 combination, with success rates of 98.6% and 95.9% respectively. On code benchmarks, it scored 73.6 on SWE-bench Verified and 51.
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Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network architecture or scheduling implementation of Genie 4.
Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network archite
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NVIDIA has released the open-weight model Nemotron 3.5 Transcribe on Hugging Face and ModelScope, integrating transcription, speaker diarization, translation, and audio question answering into a single checkpoint. It supports transcription in 40 languages, translation between 31 languages and English, and speaker labeling in 13 languages, can process recordings up to 1 hour long, and can label up to 8 speakers. The model ranks first among open-weight models on the English leaderboard of the Hugging Face Open ASR Leaderboard with an average WER of 5.33%, and achieves 2.8% AA-WER on Artificial Analysis with approximately 4B activated parameters. The simultaneously released Granary v2 covers 48 languages and 463,062 hours of speech data, and the accompanying NeMo Speech fine-tuning recipe reduced WER on held-out speakers from 22.44% to 12.17% in a medical case.
NVIDIA has released the open-weight model Nemotron 3.5 Transcribe on Hugging Face and ModelScope, integrating transcription, speaker diarization, translation, and audio question answering into a single checkpoint. It supports transcription in 40 languages, translation between 31 languages and English, and speaker labeling in 13 languages, can process recordings up to 1 hour long, and can label up to 8 speakers. The model ranks first among open-weight models on the English leaderboard of the Hugg
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Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world model architecture. It has opened beta applications to Google AI Ultra users and is also available in the Gemini API and Google AI Studio.
Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world mo
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On October 27, Liquid AI released the LFM3 series. All six 2B-parameter-class open-weight models branch from the same LFM3-1.7B-Base, covering text, vision, audio, omni-modal, and decision models. LFM3-1.7B has 1.73B parameters, a 256K token context, supports 16 languages, and adopts a Tri-Hybrid architecture with 13 layers of gated short convolutions, 5 layers of sliding-window attention, and 6 layers of global attention. It is available under the LFM Open License v1.0 on Hugging Face, the Liquid AI Playground, and via API. The company claims that LFM3-1.7B surpasses LFM2.5-2.6B with 35% fewer parameters and occupies about 1 GB of memory at 4-bit precision, but the model card states that it is not suitable for agentic coding or complex multi-step reasoning.
On October 27, Liquid AI released the LFM3 series. All six 2B-parameter-class open-weight models branch from the same LFM3-1.7B-Base, covering text, vision, audio, omni-modal, and decision models. LFM3-1.7B has 1.73B parameters, a 256K token context, supports 16 languages, and adopts a Tri-Hybrid architecture with 13 layers of gated short convolutions, 5 layers of sliding-window attention, and 6 layers of global attention. It is available under the LFM Open License v1.0 on Hugging Face, the Liqu
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Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time interaction. Internally, the model calls Gemini Omni to ensure visual realism and Gemini 3.8 Flash to maintain inter-frame consistency. It is currently being tested with a small number of early users and will later be offered through the Google AI Ultra subscription, the Gemini API, and Google AI Studio.
Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time inter
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Baseten's Base Labs has released a 2B decision model, joey-1, post-trained on Qwen3.5-2B, which directly returns labels and calibrated probabilities instead of generating text, targeting high-concurrency routing, classification, and guardrail checks. The model scores 63.30 on the public Jev Decision Index 0.4 set, the highest among models under 4B, but 8.94 points lower than the 9B elephant-1. Model APIs are priced at $0.01 per million input tokens, with a P50 latency of 20 ms for an average 2000-token request; the weights are open-sourced under the MIT license on Hugging Face and can be self-hosted on a single CUDA GPU.
Baseten's Base Labs has released a 2B decision model, joey-1, post-trained on Qwen3.5-2B, which directly returns labels and calibrated probabilities instead of generating text, targeting high-concurrency routing, classification, and guardrail checks. The model scores 63.30 on the public Jev Decision Index 0.4 set, the highest among models under 4B, but 8.94 points lower than the 9B elephant-1. Model APIs are priced at $0.01 per million input tokens, with a P50 latency of 20 ms for an average 200
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