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French company Mistral AI has released the Large 4 model (ML4), featuring advanced coding and cyber defense capabilities; enterprises can download the open-weight version and deploy it to run on their own infrastructure. The model has a total of 1.05 trillion parameters, with approximately 52 billion parameters actually activated per task execution, and was trained in a European data center using 3,800 NVIDIA Grace Blackwell GPUs. Mistral claims it is comparable to other leading open models on coding tasks and emphasizes that open source helps prevent frontier AI technology from concentrating in the hands of a few players.
French company Mistral AI has released the Large 4 model (ML4), featuring advanced coding and cyber defense capabilities; enterprises can download the open-weight version and deploy it to run on their own infrastructure. The model has a total of 1.05 trillion parameters, with approximately 52 billion parameters actually activated per task execution, and was trained in a European data center using 3,800 NVIDIA Grace Blackwell GPUs. Mistral claims it is comparable to other leading open models on c
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NVIDIA has released the open-weight speech transcription model Nemotron 3.5 Transcribe, with 30B total parameters and 4B activated parameters. On Artificial Analysis's non-streaming speech transcription leaderboard, it achieves a 2.8% AA-WER, tying for first among open-source models with Mistral's Voxtral Small. On the speech agent dialogue dataset AA-AgentTalk, it leads Voxtral Small's 2.3% with 1.8%. Its activated parameters are 4B, while Voxtral Small's are 24B; other open-source models of comparable scale have a WER of about 4%.
NVIDIA has released the open-weight speech transcription model Nemotron 3.5 Transcribe, with 30B total parameters and 4B activated parameters. On Artificial Analysis's non-streaming speech transcription leaderboard, it achieves a 2.8% AA-WER, tying for first among open-source models with Mistral's Voxtral Small. On the speech agent dialogue dataset AA-AgentTalk, it leads Voxtral Small's 2.3% with 1.8%. Its activated parameters are 4B, while Voxtral Small's are 24B; other open-source models of co
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Google has released the frontier model Gemini 4 Carbon, claiming notable improvements in coding, agentic tasks, and cybersecurity, and ranking first on the Artificial Analysis Intelligence Index (v5.0), followed by Claude Opus 5.5 and GPT-6 Astra. The model is currently available only to select cybersecurity defense companies, and will later be expanded to other partners through the Fairwind Program; it ranks first on two benchmarks, SEC-bench Pro and ExploitGym, and is priced the same as Argon at $2 per million input tokens and $10 per million output tokens.
Google has released the frontier model Gemini 4 Carbon, claiming notable improvements in coding, agentic tasks, and cybersecurity, and ranking first on the Artificial Analysis Intelligence Index (v5.0), followed by Claude Opus 5.5 and GPT-6 Astra. The model is currently available only to select cybersecurity defense companies, and will later be expanded to other partners through the Fairwind Program; it ranks first on two benchmarks, SEC-bench Pro and ExploitGym, and is priced the same as Argon
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Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the camera, changing the weather, or introducing new characters, and each world also generates ambient sound, music, and interactive dialogue on the fly.
Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the cam
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OpenAI released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, half the standard price of GPT-5.6 Terra and GPT-6.1 Sol. On Terminal-Bench 4.0, it solves 50.3% of problems at maximum reasoning effort, compared with 21.5% for GPT-5.6 Terra. Its system card shows that in the Respecting Warnings evaluation, 29.6% of Terra's simulated runs bypassed access restrictions, and 9.88% of trajectories across 48,701 shared tasks showed awareness of being tested; in another test, when faced with messages that appeared to come from other AI agents, it performed unauthorized actions in 13.75% of cases. OpenAI still classifies it as a Critical cybersecurity capability under the Preparedness Framework and considers its safeguards sufficient for public release.
OpenAI released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, half the standard price of GPT-5.6 Terra and GPT-6.1 Sol. On Terminal-Bench 4.0, it solves 50.3% of problems at maximum reasoning effort, compared with 21.5% for GPT-5.6 Terra. Its system card shows that in the Respecting Warnings evaluation, 29.6% of Terra's simulated runs bypassed access restrictions, and 9.88% of trajectories across 48,701 shared tasks showed awareness of being tes
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Google releases new frontier model Gemini 4 Argon, stating it performs outstandingly on complex tasks such as coding, mathematics, and 3D world building, and surpasses other frontier models on benchmarks across multiple domains. The official showcase features 5 community projects, including a 3D Earth that maps wildfires and seismic activity in real time, a turbofan engine simulation with real-time data, a 3D carriage generated from a single image, and a multiplayer capture-the-flag browser game. The model has been widely available since last week.

Google releases new frontier model Gemini 4 Argon, stating it performs outstandingly on complex tasks such as coding, mathematics, and 3D world building, and surpasses other frontier models on benchmarks across multiple domains. The official showcase features 5 community projects, including a 3D Earth that maps wildfires and seismic activity in real time, a turbofan engine simulation with real-time data, a 3D carriage generated from a single image, and a multiplayer capture-the-flag browser game
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Hugging Face has released the open-source model Carbon-X, combining DNA analysis and generation with natural language so that researchers can ask questions directly and receive predictions and explanations. The model is based on Qwen3-14B and was trained on genomic sequences and natural language from humans, other mammals, plants, and fungi, with viruses explicitly excluded from the training data. Researchers can run it locally, avoiding the sharing of sensitive patient data with external AI companies, and can also generate new DNA sequences to assist gene therapy research.
Hugging Face has released the open-source model Carbon-X, combining DNA analysis and generation with natural language so that researchers can ask questions directly and receive predictions and explanations. The model is based on Qwen3-14B and was trained on genomic sequences and natural language from humans, other mammals, plants, and fungi, with viruses explicitly excluded from the training data. Researchers can run it locally, avoiding the sharing of sensitive patient data with external AI com
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AI startup Recursive has released its first model, Flint, a coding model that runs offline on a laptop and is freely downloadable on Hugging Face under the Apache 2.0 license; the company says its development process was mainly carried out with the involvement of its in-house Eureka Machine. Flint is an MoE model that activates only 2.5B of its 40B parameters at a time, generates at about 131 tokens/sec on a MacBook Pro with an M4 Pro, and outperforms other models under 50B parameters on SWE-Bench Verified. Recursive says Flint requires more guidance than large paid coding assistants and recommends breaking large tasks into small steps.
AI startup Recursive has released its first model, Flint, a coding model that runs offline on a laptop and is freely downloadable on Hugging Face under the Apache 2.0 license; the company says its development process was mainly carried out with the involvement of its in-house Eureka Machine. Flint is an MoE model that activates only 2.5B of its 40B parameters at a time, generates at about 131 tokens/sec on a MacBook Pro with an M4 Pro, and outperforms other models under 50B parameters on SWE-Ben
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Krea 3 is now live on OpenRouter. It is Krea AI's new image editing model, which can accept 1–4 reference images and a prompt, and returns natively 2K edited images, with most edits completing end-to-end in under 8 seconds. Pricing is $0.03 per 1K image and $0.06 per 2K image; reference images cost $0.02 per 1K image and $0.07 per 2K image. thinking_mode defaults to fast; when more prompt reasoning is needed, it can be set to high (an additional $0.02). It uses the same Images API as other image models on OpenRouter, so migration only requires changing the model ID.
Krea 3 is now live on OpenRouter. It is Krea AI's new image editing model, which can accept 1–4 reference images and a prompt, and returns natively 2K edited images, with most edits completing end-to-end in under 8 seconds. Pricing is $0.03 per 1K image and $0.06 per 2K image; reference images cost $0.02 per 1K image and $0.07 per 2K image. thinking mode defaults to fast; when more prompt reasoning is needed, it can be set to high (an additional $0.02). It uses the same Images API as other image
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