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All news · Today7 items

All AI news

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.

10/13Tue
  1. The Decoder83

    Meta releases Muse Wonder models with gains in coding and agent benchmarks

    Meta released Muse Wonder and Muse Wonder Full, scoring 52 and 56 on the Artificial Analysis Intelligence Index v4.3, versus 48 for Muse Spark 1.3. Both support a one-million-token context window and text, image, video, and audio inputs, with stronger coding and agent results but weaker factual knowledge than leading competitors. Muse Wonder is available through Meta's API and Muse Code at higher prices than its predecessor; Muse Wonder Full is currently limited to Muse Code users.

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

  5. 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》

  6. Alexandr Wang · X82

    Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores

    Meta has released Muse Wonder and Muse Wonder Full, according to Artificial Analysis in the post quoted by Alexandr Wang. At max reasoning effort, they score 52 and 56 on the Artificial Analysis Intelligence Index v4.3, compared with Muse Spark 1.3’s 48, following a release gap of 6 weeks. Muse Wonder is available through Meta’s first-party API and Muse Code, while Muse Wonder Full is limited to Muse Code users; both have 1M-token context windows.

    Why it matters: Artificial Analysis’s comparison highlights a tradeoff between Muse Wonder’s improved benchmark performance and its higher cost per task relative to Muse Spark 1.3 despite lower output token usage.

  7. TechCrunch · AI83

    Meta releases frontier models Muse Wonder and Muse Wonder Full

    Meta’s Superintelligence Lab released Muse Wonder and Muse Wonder Full on Monday, larger models described as more capable than Muse Spark. Meta reports benchmark scores comparable to Fable 5.1 and GPT-6 Astra and emphasizes information retention through “active memory.” Wonder costs $4.00 per million input tokens and $20.00 per million output tokens through the Meta Model API; Wonder Full is available only to Muse Code subscribers. Both models will power the Muse agent.

    Why it matters: The split between API access for Wonder and subscriber access for Wonder Full gives developers a concrete basis for comparing integration options within Meta’s new model lineup.

  8. 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》

  9. 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》

  10. 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

  11. The Verge · AI65

    Meta launches Muse Wonder and Muse Wonder Full AI models

    Meta launched Muse Wonder and Muse Wonder Full, available to Muse Code subscribers starting today; Wonder is also accessible through the Meta Model API. Meta claims internal benchmark testing shows the models can rival OpenAI’s GPT-6 Astra and Anthropic’s Claude Opus 5.5 and Claude Fable 5.1. The company plans to power its Muse AI agent with Wonder, starting with subscribers, but has provided no timeline.

  13. Alexandr Wang · X28

    MUSE WONDER this is the culmination of over a year of research and infrastructure work in msl since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆 see our model's improvements on the artificial analysis index:

    MUSE WONDER this is the culmination of over a year of research and infrastructure work in msl since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆 see our model's improvements on the artificial analysis index:

  14. 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》

10/12Mon
  1. Satya Nadella · X73

    Microsoft introduces Maia 300 and plans multi-gigawatt Maia deployments

    Microsoft is introducing Maia 300, which Satya Nadella says delivers 40% more tokens per watt compared to leading GPU-based systems. Starting next calendar year, Microsoft will scale its Maia family to multi-gigawatt deployments, making it the primary inference system for its own products and services. Microsoft is already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot, with a goal of building on full-stack efficiency gains while continuing to bring ecosystem innovations into its fleet.

    Why it matters: Making Maia the primary inference system for Microsoft’s own products and services gives its stated efficiency gains a concrete deployment context.

  2. 量子位47

    Zhipu’s GLM-5.3-Highspeed Model Reportedly Reaches 490 Tokens per Second

    Zhipu has added the GLM-5.3-Highspeed model to Zcode, where it is being gradually rolled out to subscribers at random. A user reported a generation speed of 490 tokens per second; the article says the model is currently available for testing in Zcode 3.15.1. The reported speed has not been independently confirmed, and the author says they could not access the model.

  3. 雷锋网57

    Microsoft releases Qwen-based Microsoft-Decision-1 and tests applications across domains

    Microsoft released Microsoft-Decision-1, a decision model post-trained from Qwen3.5-9B, and says it outperforms LLMs and decision models including Jev 1.13.0 on latency and accuracy in structured decision tasks. Its Xbox research team has used it to process more than 10,000 player feedback entries, while CEO Satya Nadella says Microsoft is testing applications across domains, including incident response, quality control, and scientific discovery. The report describes decision models as smaller, faster models that output predictions, probabilities, and confidence scores rather than natural language.

10/11Sun
  2. 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.

  3. 量子位78

    Google releases Nano Banana 2.1 image model with 4K output

    Google released Nano Banana 2.1, an upgraded image generation model with 4K output, mask-based editing and improved subject consistency. According to Arena, it gained about 61.7 points on average across text-to-image, multi-image editing and single-image editing, and Google halved API prices for 1K and 2K images while cutting 4K by about 25%. It is available in the Gemini app and Google AI Studio, with 50 free credits daily.

    Why it matters: The piece rounds up Arena ranking gains, API price cuts and early user tests of Nano Banana 2.1, including reported watermark and repeated-edit issues.

10/10Sat
  1. The Decoder66

    Microsoft launches Decision-1 decision model based on Qwen3.5-9B

    Microsoft released Decision-1, a decision model for classifications, evaluations and routing decisions, built on Qwen3.5-9B. Microsoft says it tops 36 benchmarks covering nearly 150,000 questions with 83.5% accuracy and 85 ms latency, and is 2.5 times faster than runner-up H2O-Lightning-4B. It is available through Microsoft Foundry and OpenRouter at $0.042 per million input tokens, with output tokens free.

  2. 雷锋网67

    Step 5 Preview Tops OpenRouter Trending Ahead of October 15 Open-Source Release

    StepFun's flagship base model Step 5 Preview reached the top of OpenRouter's Trending list and second place on its daily ranking, with an official open-source release set for October 15. The sparse MoE model has 600 billion total parameters and about 27 billion activated per token, and Artificial Analysis gives it a composite intelligence index of 44, placing it in the global open-source top three.

  3. Artificial Analysis · X66

    HiDream-O1-Video-1.0 debuts at #6 on Artificial Analysis Image to Video with Audio Leaderboard

    HiDream-O1-Video-1.0, HiDream’s new video model, debuts at #6 on the Artificial Analysis Image to Video with Audio Leaderboard, just behind Dreamina Seedance 2.0 720p. HiDream positions it as a native omnimodal model built for physical consistency, generating 1080p videos of 5 to 20 seconds with natively synchronized audio and scene-dependent duration. It is available through vivago R1 Studio and the HiHarness API, where 1080p video with audio costs $5.80 per minute, about $0.10 per second.

  4. Satya Nadella · X49

    Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

    Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

  5. Artificial Analysis · X55

    HeyGen Voice tops Artificial Analysis’s Controlled Voice TTS Arena leaderboard

    HeyGen Voice ranks #1 on Artificial Analysis’s Controlled Voice TTS Arena leaderboard, which evaluates models using the same 8 cloned voices across US and UK English. Its Elo is 1,201 across 1,468 arena appearances, ahead of Qwen-Audio-3.1-TTS-Plus at 1,182 and Eleven v4 Turbo at 1,166. HeyGen Voice scores 83.1% on Pronunciation Robustness, ranking #10 of 29 models; it costs $30/1M characters and generates 40 characters per second of generation time.

10/9Fri
  1. Qwen · X65

    Qwen releases Qwen-Image-2.1-Turbo, generating and editing images with 8-step denoising and open weights

    Qwen has released Qwen-Image-2.1-Turbo, based on the same 7B visual generation architecture as Qwen-Image-2.1, requiring only 8 denoising steps to generate and edit images, with weights now open on ModelScope and Hugging Face.

    Why it matters: Qwen's image model gains a Turbo accelerated version, with 8-step sampling and open weights offering a generation and editing path that can be integrated directly.

  2. vLLM · X40

    vLLM Semantic Router team ships Decision 2.0 for single-pass routing and classification

    Great work from the vLLM Semantic Router team on Decision 2.0. Multiple questions about one input, answered in a single forward pass with per-option probabilities. Useful for routing and classification. Quoted post by @XunzhuoLiu: In every size. Decision 2.0: six open decision models, 0.6B to 27B. On the #Jev Decision Index 0.3, each one tops the same-size open models we lined it up against. #Trending collections on Hugging Face 🤗 Decision 2.0: https://huggingface.co/collections/vllm-sr/decision-20 Vela 2.0: https://huggingface.co/collections/vllm-sr/vela-20

  3. Artificial Analysis · X74

    Grok Imagine Video 1.5 Lite ranks #17 in Artificial Analysis video benchmarks

    Artificial Analysis reports that Grok Imagine Video 1.5 Lite ranks #17 on both AA-Video-T2V v2.0 and AA-Video-T2V-Silent v2.0, ahead of Google's Veo 3.1 at about a third of its price. Its median generation time of 60.5 seconds for a 10 second 1080p clip places it on the quality and speed Pareto frontier. SpaceXAI prices 1080p output at $0.14 per second ($8.40 per minute), with availability through the SpaceXAI API, fal at the same prices, and Vercel AI Gateway.

  6. Aravind Srinivas · X50

    Perplexity Decider V1.1 ranks first on DecisionBench with the lowest cost

    Aravind Srinivas says Perplexity Decider ranks first on DecisionBench and has the lowest cost. https://twitter.com/rohanatlan/status/2108233674538041588 The quoted post by @rohanatlan reports that Decider V1.1 achieved 93.9% accuracy across 949 shared text cases, with 534 ms median latency and $0.016 / 1k decisions, and says they plan to try it for their product use cases. Latest results: https://decisionbench.ai

10/8Thu
  1. Hugging Face Blog40

    TII launches Falcon-ASR, a 1.6B-parameter Arabic speech recognition model focused on Emirati dialects

    Abu Dhabi's Technology Innovation Institute (TII) released Falcon-ASR, a 1.6B-parameter speech recognition model focused on Arabic and Emirati dialects, with support for English, French, Spanish, and Portuguese as well. Its average WER across six Arabic test sets is 20.92%, 2.25 percentage points below the best public result of 23.17% in the leaderboard snapshot used. In an internal Emirati dialect evaluation, it achieved a 22.73% WER and 10.19% CER, outperforming Qwen3-Omni.

  2. 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.

  3. 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.

  5. Simon Willison78

    Anthropic releases Claude Haiku 5.5 at GPT-6 Luna pricing

    Anthropic released the fast, low-cost Claude Haiku 5.5 at $0.10 per million input tokens and $0.50 per million output tokens, exactly matching GPT-6 Luna, released by OpenAI last month. Above 100,000 tokens, Haiku 5.5 rises to $0.50/$2.50, while Luna does not rise to $0.20/$0.75 until 272,000 tokens.

    Why it matters: The author tested Haiku 5.5 pricing, tokenizer changes, and the cost and latency of different reasoning tiers, offering a basis for weighing it against GPT-6 Luna.

  6. 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.

  7. 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》