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Only Models#Multimodal
  1. Google DeepMind90

    Google DeepMind releases Gemini 4 Hydrogen, a faster Gemini 4 model for coding and agentic workflows

    Google DeepMind introduced Gemini 4 Hydrogen, a Gemini 4 model built for fast everyday coding and agentic execution rather than the long-horizon reasoning of Gemini 4 Carbon and Argon. It scores 51 on the Artificial Analysis Intelligence Index at its default high thinking level versus 50 for Argon, reaches 54 at a new xhigh setting, and is priced flat at $1.50 per million input tokens and $7.50 per million output tokens across its 1 million-token context window. Google also launched Orchestrator in Google Antigravity, which switches between models like Carbon and Hydrogen within a session and reached near-Carbon task success on Terminal-Bench 4.0 while using 24% less quota and finishing 19% faster.

    Why it matters: Google's Gemini 4 Hydrogen targets fast everyday coding and agentic work, with flat $1.50/$7.50 per million token pricing across a 1M context window and a new Orchestrator that switches between Gemini 4 models.

  1. The Decoder80

    Google DeepMind launches Gemini Decisions API and Gemini Decision 1 model

    Google DeepMind introduced the Gemini Decisions API, built for closed-ended decisions such as yes/no questions, multiple choice, and scale-based ratings, with the underlying Gemini Decision 1 model processing up to 1,000 independent questions in a single pass across text, images, audio, video, and PDFs. It returns probabilities with confidence values in 150 to 250 milliseconds and costs $0.10 per million input tokens with no output-token charge, which Google says is about five times cheaper than Gemini 3.5 Flash-Lite. The API is available now through Google AI Studio, with integrations for OpenRouter, LangChain, and Vercel rolling out, and Google says it already uses it internally for model routing in Gemini Notebook, design prototyping in Stitch, and safety checks in Google Search.

    Why it matters: Google's entry into closed-ended decision APIs shows how vendors are packaging fast, low-cost scoring for routing and safety checks, with pricing and latency figures for comparison.

  1. Simon Willison82

    Simon Willison tests Gemini 4 Carbon in Antigravity IDE as Google opens access to all users

    Gemini 4 Carbon, announced two weeks ago for a subset of cyber defenders, is now available to everyone at $2/million input and $10/million output, with prices scheduled to double to $4/$20 on December 1st. Simon Willison tested it in Google's Antigravity IDE, generating a Three.js animation of a mech stomping through New York City using OpenStreetMap data, and noted that Google CEO Sundar Pichai highlighted Antigravity's /swarm feature building an open-world 3D game with Blender assets, WebGL shaders and Lyria music.

    Why it matters: Simon Willison tests Gemini 4 Carbon's coding and 3D generation in Antigravity IDE, offering a hands-on look at Google's newest model before its price doubles on December 1st.

  1. Claude YouTube78

    Anthropic releases Claude Fable 5.2 for ambitious technical work

    Anthropic released Claude Fable 5.2, a model designed for the most daunting technical challenges and ambitious open-ended projects, with improvements in coding, reasoning and vision. The company recommends starting with Opus 5.5 for most coding and knowledge tasks; Fable 5.2 is available today on Pro, Max, Team and Enterprise plans.

    Why it matters: Claude Fable 5.2 targets ambitious open-ended technical work, with stated gains in coding, reasoning and vision, while Opus 5.5 remains the recommended default for most coding and knowledge tasks.

  1. Meta AI Research Blog78

    Meta releases Muse Ember, its smallest and most efficient model for agent tasks

    Meta released Muse Ember, its smallest and most efficient model, aimed at the repetitive work agents do all day such as tool calls, coding subtasks, routing, extraction and long document parsing. Meta says it matches Claude Haiku 5.5's best score at about a third of the cost and beats every GPT-6 Luna setting, at $0.10 per million input tokens and $0.50 per million output tokens. It ships with a 1M-token context window, up to 512K output tokens, native text, image, audio and video input, and is available today on Muse Code and the Meta Model API as muse-ember-1.0.

    Why it matters: Meta's smallest model targets the high-volume agent steps, and its cost-per-task comparison against Claude Haiku 5.5 and GPT-6 Luna shows where the efficiency claim comes from.

  1. Google DeepMind78

    Google DeepMind releases Gemini Omni 1.2 Flash with 15-second clips and 30% lower price

    Google DeepMind rolled out Gemini Omni 1.2 Flash, now generally available across the Gemini API and Gemini for business, with native 15-second video generation, multi-turn conversational editing and stronger reference following. The price drops 30% from Gemini Omni 1.1 to $0.07 per second for 720p video, and users can draft at 360p or 720p before upscaling to 1080p or 4K. Clips can be set from 3 to 15 seconds in one-second increments, and outputs carry an imperceptible SynthID watermark.

    Why it matters: Gemini Omni 1.2 Flash raises native clip length to 15 seconds and cuts the price 30% to $0.07 per second of 720p video, with multi-turn conversational editing now generally available.

  2. Google Blog · AI80

    Google releases Gemini Omni 1.2 Flash with 15-second clips and a 30% price cut

    Google DeepMind rolled out Gemini Omni 1.2 Flash and made it generally available across the Gemini API and Gemini for business. The model generates and edits native clips up to 15 seconds, up from 10 seconds in Omni 1.1, supports multi-turn conversational editing, and holds character, product, and style references more consistently; 720p video now costs $0.07 per second, 30% less than Omni 1.1. Outputs carry a SynthID watermark, and the model is rolling out in Flow, Google Vids, the Gemini app, and Google Ads.

    Why it matters: Gemini Omni 1.2 Flash cuts the price 30% to $0.07 per second for 720p video while extending native clips to 15 seconds, giving teams producing video at scale a cheaper option to compare against prior versions.

  1. Preferred Networks News71

    PFN releases PLaMo 3 Translate open-weight translation LLM for edge devices

    Preferred Networks released PLaMo 3 Translate, a translation-specialized LLM used in its PLaMo Translation service, as an open-weight model on Hugging Face on November 5. 8B, 2B, 8B and 31B) and supports 53 languages including Japanese and English, running on smartphones, laptops and internal servers without a cloud connection.

    Why it matters: PFN releases a translation-specialized LLM in four sizes from 0.8B to 31B, letting companies and individuals run 53-language translation on-device without cloud access.

  1. Meta AI Research Blog88

    Meta releases Muse Spark Open, an 816B open-weight multimodal model that runs on two Mac Studios

    Meta released the weights for Muse Spark Open, an open-weight natively multimodal model with 816B total parameters (42B active) and a 1M-token context window, positioned for coding and agentic work. It is the first model in its class to run on a desktop using two Apple M5 Ultra Mac Studios with the MLX framework, and it is available through API partners including Baseten, Fireworks AI, Groq, Modal, Nebius, OpenRouter and Together AI, with weights on Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden and Microsoft Foundry Models. Meta says the model ships with auto-tunable Helion GPU kernels in SGLang, delivering 1.03-3.95x kernel-level speedups on NVIDIA and AMD GPUs and a 3% end-to-end speedup on AMD MI350.

    Why it matters: Meta releases open weights for an 816B-parameter multimodal model that runs on two Mac Studios, giving developers a local option for long-horizon coding and agentic tasks.

  1. Mistral AI82

    Mistral launches Mistral Large 4 preview, a 1T-parameter multimodal model with weights due this month

    Mistral has launched a public preview of Mistral Large 4, a 1 trillion-parameter natively multimodal model with 52 billion active parameters, available now through the Mistral Studio API. Mistral says the model is competitive with the strongest open-source models and outperforms other open-weight models from the US and Europe, scoring 82% on an Artificial Analysis Cyber Index vulnerability reproduction and patching test and 49.8% on its combined Coding Agent Index. The weights are set to be released by the end of the month, after red-teaming with cybersecurity partners and authorities; Mistral says the model was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in its own European datacenters.

    Why it matters: Mistral's largest model yet claims open-weight leadership in cybersecurity and agentic coding, with weights promised by month's end.

  1. MiniMax Blog71

    MiniMax releases Music 3.0, an open-weights music generation model for full songs up to five minutes

    MiniMax introduced Music 3.0, an open-weights music generation model that composes, arranges and produces a complete song of up to five minutes from a creative concept and optional lyrics in a single generation. The pipeline pairs an 8B Global LLM initialized from Qwen3.5-8B with a 0.6B Local LLM, fuses their continuous hidden states to condition a 2.4B flow-matching module and a 123M Flow-VAE, and uses eight-layer RVQ plus Structured Captions that describe emotion, instrumentation and vocal delivery over time. MiniMax says this yields more accurate interpretation of creative intent, fuller arrangements and clearer, more natural vocals.

    Why it matters: MiniMax's architecture breakdown shows how an 8B global LLM paired with a 0.6B local model and flow-matching stack targets the long-song coherence problem.

  1. MiniMax Blog82

    MiniMax launches H3, a general-purpose multimodal generation model with native stereo video at 2K

    MiniMax launched H3, a general-purpose multimodal generation model that understands text, images, video and audio as a unified context and generates video with native stereo sound up to 15 seconds at 2K resolution. The company says 2K output costs less than a third of mainstream models per second, and it plans to open the model weights in the coming days subject to applicable laws and regulations. H3 is built on Contextual Omni Representation, H3-VAE, H3-Omni Transformer and In-Context Regeneration, and MiniMax says a full technical report is coming soon.

    Why it matters: MiniMax's H3 unifies text, image, video and audio generation in one model and claims 2K pricing below a third of mainstream models, with weights promised soon.

  1. MiniMax Blog87

    MiniMax M3 released with 1M context, frontier coding and native multimodality

    MiniMax released M3, an open-weight model it says is the first to combine frontier coding and agentic performance, a 1M-token context window, and native image and video input. M3 uses MiniMax's new MSA sparse attention architecture, which the company reports cuts per-token compute at 1M context to 1/20 of the previous generation and speeds prefill by more than 9x and decoding by more than 15x. It scores 59.0% on SWE-Bench Pro, 66.0% on Terminal-Bench 2.1 and 74.2% on MCP Atlas, and is available through MiniMax Code, the Token Plan and the API, with weights and a technical report promised within 10 days.

    Why it matters: MiniMax M3 combines a 1M-token context, frontier coding and agentic scores, and native image and video input in one open-weight model, with MSA cutting per-token compute at long context.

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