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#Agent

All collected and published items, ordered by time. Picks are a selected subset.
Models

New models and versions, open weights, and changes in capability and pricing, with their evaluations.

10/16Fri
  1. Hugging Face Blog83

    Reflection releases Beam, a 501B open model for coding and agentic work

    Reflection released Beam on Hugging Face, a 501B MoE model with 23B active parameters per token, a 1M-token context window, and an Apache 2.0 license. The text-only model targets coding and agentic work, with BF16, FP8, and NVFP4 checkpoints and day-0 support in transformers, vLLM, and SGLang. Hugging Face provides deployment and post-training recipes alongside its own task evaluations and demos.

    Why it matters: The deployment guidance distinguishes active computation from total weight memory, helping teams assess hardware requirements for running and adapting a sparse model with a long context window.

  2. The Decoder77

    Meta releases Muse Spark Open for coding and agentic tasks

    Meta has released Muse Spark Open, an open-weight model with 816 billion parameters (42 billion active), up to one million tokens of context, and text, image, video, and audio support. Meta reports leads over Qwen 3.8, GLM 5.3, and Kimi K3 in several benchmark categories, while trailing some competitors in coding. Weights are on Hugging Face; use requires the label "Built with Muse Spark Open," and API providers earning more than $20 million annually need a separate agreement with Meta.

    The same story is shown in the picks as 《Meta releases Muse Spark Open, an open-weight multimodal mixture-of-experts model》

  3. Ollama · X79

    Meta releases Muse Spark Open, with Ollama availability coming shortly

    Meta announced Muse Spark Open, calling it the most capable US open-weight model to date and describing it as built for coding and agentic work. Meta lists 816B total / 42B active parameters, a 1M token context window, and native text, image, video, and audio support. Ollama welcomed the release and said the model will be available on Ollama shortly. https://twitter.com/AIatMeta/status/2110779754274292212

    The same story is shown in the picks as 《Meta releases Muse Spark Open, an open-weight multimodal mixture-of-experts model》

  4. The Decoder81

    Nvidia releases Nemotron 3.5 Super VL for continuously running enterprise AI agents

    Nvidia released Nemotron 3.5 Super VL, an open multimodal model with 120 billion parameters and 12 billion active per token, for continuously running enterprise agents. Nvidia says it approaches Nemotron 3 Ultra’s accuracy on specified agent tasks with about one-fifth the parameters, and is releasing weights, datasets, and training recipes. The accompanying Nemotron 3.5 Bolt 74B-A9B 24GB targets local agents, while Bolt E4B 4GB is planned for later this month.

    Why it matters: The deployment details clarify how quantization, caching, and hardware requirements shape the practical tradeoffs of running continuous enterprise agents on company infrastructure.

10/15Thu
  1. NVIDIA Blog81

    NVIDIA Expands Nemotron Family With Super VL and Bolt Open Models

    NVIDIA released Nemotron 3.5 Super VL, an open 120-billion-parameter model for multimodal agents, and Nemotron 3.5 Bolt 74B-A9B 24GB for local agentic workloads; Bolt E4B 4GB is coming Oct. 23. Super VL targets tool use, business workflows and visual document understanding, with open weights, datasets and training recipes. Bolt 74B-A9B uses native 2-bit quantization to fit in 24GB of memory, while Bolt E4B targets physical and conversational agents.

    Why it matters: Open weights, datasets and training recipes give organizations a path to adapting agents to their own workflows while meeting local deployment and data residency requirements.

10/14Wed
  1. Hugging Face Blog79

    Liquid AI releases LFM2.5-24B-A2B for fast, private on-device agents

    Liquid AI released LFM2.5-24B-A2B, an open-weight reasoning model with 24B total parameters and 2B active parameters, for on-device agents that reason and call tools. Its context window expands from 32K to 131K tokens, and both the reasoning and Base versions are available on Hugging Face. Liquid AI reports 184 tokens/s on an Apple M5 Max and competitive tool-use results, while acknowledging that larger models retain advantages on knowledge-heavy and coding benchmarks.

    Why it matters: The benchmark comparison helps distinguish workloads suited to local deployment, with strong tool use and instruction following alongside weaker knowledge and coding results than some larger models.

10/13Tue
  1. Latent Space84

    Meta launches Muse Wonder and Muse Wonder Full frontier models

    Meta Superintelligence Labs released Muse Wonder and Muse Wonder Full, its second-generation model family for personal and professional agentic work. Latent Space reports that Wonder is available through the Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Artificial Analysis gives Wonder Full and Wonder Intelligence Index v4.3 scores of 56 and 52, respectively, versus Opus 5.5’s 58; Wonder supports a 1M context window and text, image, video, and audio inputs, with text-only output.

    Why it matters: The benchmark breakdown compares Wonder variants with competing models on agentic performance and token usage, showing how their relative standing changes across tasks rather than a single ranking.

  4. 宝玉 · X80

    Meta releases Muse Wonder for developers as consumer access remains unclear

    Baoyu reports that Meta released Muse Wonder and Muse Wonder Full on October 12, with Muse Wonder available today through Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Meta’s blog says consumer access is coming soon, whereas Zuckerberg says subscribers can use it today. The models support a 1 million token context window and multimodal input with text output. Meta reports strengths in sustained agentic work, coding, and memory, but its comparisons include internal benchmarks and competitor runs that may not be optimally configured.

    The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》

  5. 宝玉 · X82

    Meta launches Muse Wonder with developer access and conflicting consumer availability statements

    Meta released Muse Wonder and Muse Wonder Full on October 12, according to Baoyu’s account of the announcement. Developers can access Muse Wonder through Meta Model API or Muse Code, while Full is available to Muse Code subscribers; Meta’s blog and Zuckerberg’s X post differ on consumer availability. The models support a 1 million Token context window and multimodal input with text output, while Meta’s reported benchmarks show strengths in sustained agentic and coding tasks alongside weaker results elsewhere.

    The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》

  6. Artificial Analysis · X81

    Meta releases Muse Wonder and Muse Wonder Full with higher Artificial Analysis scores

    Meta has released Muse Wonder and Muse Wonder Full, which Artificial Analysis reports score 52 and 56 on its Intelligence Index v4.3 at max reasoning effort, versus 48 for Muse Spark 1.3 (max). Muse Wonder Full improves across all ten evaluations, with the largest gains in agentic evaluations. Muse Wonder is available through Meta’s first-party API and Muse Code at launch, while Muse Wonder Full is limited to Muse Code users; Muse Wonder costs $4.52 per Intelligence Index task.

    The same story is shown in the picks as 《Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores》

  7. Alexandr Wang · X21

    MUSE WONDER 🍉 this model was developed to power personal agents. three highlights: - ACTIVE MEMORY: best memory across days/weeks/months - ACTIVE FOCUS: gets your tasks done - DOMAIN EXPERTISE: sota in finance & legal, strong in health

    MUSE WONDER 🍉 this model was developed to power personal agents. three highlights: - ACTIVE MEMORY: best memory across days/weeks/months - ACTIVE FOCUS: gets your tasks done - DOMAIN EXPERTISE: sota in finance & legal, strong in health

  9. AI at Meta · X70

    Meta introduces Muse Wonder and Muse Wonder Full for agentic tasks

    Meta introduces Muse Wonder and Muse Wonder Full, describing them as its most capable models yet and frontier models built for personal and professional agentic tasks. Muse Wonder is available today via the Meta Model API and Muse Code. Muse Wonder Full is available today for Muse Code subscribers. Muse Wonder will also soon power experiences in Meta’s personal agent product, Muse, rolling out first to subscribers.

    The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》

10/11Sun
  1. The Decoder66

    Odyssey opens public preview of its Odyssey-3 world model

    Odyssey has launched a free public research preview of Odyssey-3, a world model that generates interactive environments from text prompts and runs in real time on an autoregressive diffusion transformer. The base model has 14 billion parameters and outputs 832 × 480 video, while Odyssey-3 Pro supports 1280 × 720. Its reported 66.1-point Physics-IQ Verified score came from a single run using a selection method, below the benchmark's four-run requirement.

10/9Fri
10/8Thu
  1. Latent Space82

    Anthropic releases Claude Haiku 5.5 at GPT-6 Luna pricing

    Anthropic released Claude Haiku 5.5, the first Haiku-series update in about a year. Its pricing matches OpenAI's GPT-6 Luna. On the same day, Anthropic also cut prices for Sonnet 5.5 and its subscription plans.

    Why it matters: The report brings together Haiku 5.5 pricing, independent evaluations, and token-usage data to help assess cost tradeoffs for small models in agent workflows.

  2. 量子位80

    Anthropic releases Claude Haiku 5.5, matching GPT-6 Luna on benchmarks while cutting prices by 90%

    Anthropic released Claude Haiku 5.5. Its official benchmark scores exceed GPT-6 Luna across the board, making it the new small-model gatekeeper, replacing DeepSeek V4.1 Flash and GLM-5.3-Flash.

    Why it matters: The source provides Haiku 5.5 benchmark scores, tiered pricing, and a migration checklist, helping readers judge which execution-layer tasks it can take on.

  4. The Decoder82

    Anthropic releases Claude Haiku 5.5 with prices cut by up to 90%

    Anthropic released Claude Haiku 5.5, its fastest and least expensive small model so far. Average prices are about 75% lower than Haiku 4.5; for prompts under 100,000 tokens, prices are up to 90% lower, while prompts above that threshold cost five times as much.

    Why it matters: The source provides Haiku 5.5's pricing table and comparisons across several benchmarks, helping readers assess the tradeoffs for cost-sensitive tasks.

  5. The Decoder87

    OpenAI releases GPT-6; ChatGPT switches to interactive charts and buttons

    OpenAI released GPT-6 to all ChatGPT users with a new feature called Intelligent UI. Instead of answering only in plain text, the model can generate interactive interfaces with graphics, buttons, charts, and forms based on the question. It can display comparisons side by side, turn explanations into interactive charts, and build small tools such as savings calculators or games directly in a conversation.

    The same story is shown in the picks as 《OpenAI 在 ChatGPT 全球上线 GPT-6 并推出 Intelligent UI》

10/7Wed
10/6Tue
  1. Mistral AI80

    Mistral launches public preview of Mistral Large 4, a 1-trillion-parameter multimodal model

    Mistral released a public preview of Mistral Large 4, a natively multimodal model with 1 trillion parameters and 49 billion active parameters. Its weights will be opened at the end of the month.

    Why it matters: Mistral outlined the open-weight release schedule for its 1-trillion-parameter multimodal model and its investment in European compute, allowing comparison with mainstream open models.

  4. AWS Machine Learning Blog62

    GLM 5.3 launches on Amazon Bedrock

    Zhipu AI (Z.ai)'s GLM 5.3 is now available on Amazon Bedrock. The 753B-parameter mixture-of-experts model targets coding and long-horizon agent tasks and is offered through a fully managed API with cross-region inference, prompt caching, and service tiers. It is currently available to eligible enterprise customers.

    Why it matters: The source describes how to access GLM 5.3 on Bedrock and use prompt caching, helping readers assess the cost impact of managed inference for coding and long-horizon agent workflows.

  5. TechCrunch · AI72

    Reflection releases open-weight Beam model to compete with Chinese open models

    Reflection AI officially released its first frontier open-weight model, Beam, saying it performs comparably to leading Chinese open models on advanced reasoning benchmarks with 3–4 times less inference compute. Beam is a 501-billion-parameter, 23-billion-active-parameter text model, pretrained on 23.8 trillion tokens with a 1-million-token context window. The company says it matches Z.ai's GLM-5.2 and exceeds current leading Western open models.

  6. Ollama · X65

    Reflection AI announces Beam, a 501B-parameter agentic open model

    Reflection AI introduced Beam, described as a highly efficient agentic open model with 501B total parameters and 23B active parameters. The company says it advances the Western open frontier on coding and agentic tasks and was trained end-to-end from scratch, with full weights to be released this month. Ollama said more US models are coming to its platform.

    Why it matters: Reflection AI's Beam is presented as an efficient agentic open model with 501B total and 23B active parameters, giving readers a concrete comparison point for open-weight coding and agentic models.

10/3Sat
10/2Fri
  1. 量子位82

    Google launches Gemini 4 Argon, tops multiple leaderboards at about half Astra's cost

    Google released its next-generation flagship model, Gemini 4 Argon. It scored 77.9% on DeepSWE v1.1, ahead of Claude Opus 5.5 at 74.2% and GPT-6 Astra at 74.1%, and ranked first on Text Arena with 1,525 points.

    Why it matters: Google's new flagship tops several leaderboards and publishes cost and maximum output-token figures, helping readers assess its position against GPT and Opus.

10/1Thu
  1. Latent Space82

    Google DeepMind releases Gemini 4 Argon with up to 1M output tokens

    Google DeepMind released Gemini 4 Argon for coding, enterprise knowledge work, and cyber defense. It is initially available to government users and trusted cybersecurity professionals in the Fairwind program, before expanding to developers, businesses, and consumers.

    Why it matters: This summary combines Gemini 4 Argon's benchmark results, pricing, and differences in third-party evaluations, enabling comparison with Astra and Opus 5.5.

  2. The Decoder78

    Google releases Gemini 4 Argon, matching OpenAI and Anthropic but without a clear lead

    Google released frontier model Gemini 4 Argon, matching OpenAI and Anthropic on several benchmarks without a clear lead. It is initially available to 'trusted cyber defenders' in the Fairwind program and Google's internal teams before expanding to developers, businesses, and consumers. Promotional API pricing is $2 per million input tokens and $10 per million output tokens.

    Why it matters: This summary compares third-party and human-preference leaderboards, scores, token use, and pricing for Gemini 4 Argon against OpenAI and Anthropic.

  3. Google DeepMind88

    Google DeepMind releases frontier model Gemini 4 Argon

    Google DeepMind released frontier model Gemini 4 Argon, initially making it available through the Fairwind Program to trusted cybersecurity defenders before gradually expanding access. Pricing starts at $2 per million input tokens and $10 per million output tokens.

    Why it matters: Gemini 4 Argon raises the maximum output to 1M tokens and reports multiple benchmark results and internal deployment data, offering a view of its limits on long-running workflows.

  5. Google AI · X62

    Google announces Gemini 4 Argon frontier model

    Google announced Gemini 4 Argon, a new frontier model built to sustain deep reasoning across complex, long-horizon workflows, with frontier performance in software engineering, enterprise knowledge work such as legal and finance, and cybersecurity defense. Google is expanding the model's output token limit to 1M tokens. Argon is rolling out to trusted cyber defenders in the Fairwind Program, with broader availability planned as soon as possible.

9/30Wed