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Tuesday

  1. David Singleton

    Muse Wonder model released, aimed at personal agents and made available first to subscribers

    The Muse Wonder model has been released, positioned to power personal agents, and has been made available first to subscribers. The model includes three capabilities: Active Memory, Active Focus, and domain expertise. The company says its memory spans day, week, and month scales, and that it achieves SOTA in finance and legal domains and performs strongly in health. David Singleton said he has been using it for some time and believes that under Active Focus and Active Memory the model works harder and calls on memory more precisely.

    The Muse Wonder model has been released, positioned to power personal agents, and has been made available first to subscribers. The model includes three capabilities: Active Memory, Active Focus, and domain expertise. The company says its memory spans day, week, and month scales, and that it achieves SOTA in finance and legal domains and performs strongly in health. David Singleton said he has been using it for some time and believes that under Active Focus and Active Memory the model works hard

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    #analysis#Product updates#Agents#OpenAI

Wednesday

Friday

Saturday

  1. Story2 reports · 1 facts

    Elorian releases its first AI model, Glimpse

    On October 17, 2026, Elorian released its first AI model, Glimpse. According to Testing Catalog, Glimpse can, during its thinking process, return to a specific point in a video, zoom in on details, or replay half a second of video at a higher frame rate before answering. Elorian's own testing shows that Glimpse outperforms GPT-6 Astra in reading scientific charts and describing short videos; in a simulated task of planning for a robotic arm to place cream cheese into a bowl, Glimpse cost $0.035, compared with $0.249 for GPT-6 Astra; in a demonstration, Glimpse solved 5 mazes of increasing difficulty, while Gemini 3.8 Flash solved 1/5. Another report the same day said that Elorian positions Glimpse as the first visual reasoning model, used to compare scene changes at different points in a video, and calls this frame-based reasoning visual thinking; during its reasoning process it can return to the source video, crop regions, extract specified frames, or run code to measure and compare what it sees, a mechanism called visual scratch space; co-founder Andrew M. Dai said it has frontier performance competitive with Astra on key public visual reasoning benchmarks. At present, there have been no further evidence-supported developments since the model's release.

    On October 17, 2026, Elorian released its first AI model, Glimpse. According to Testing Catalog, Glimpse can, during its thinking process, return to a specific point in a video, zoom in on details, or replay half a second of video at a higher frame rate before answering. Elorian's own testing shows that Glimpse outperforms GPT-6 Astra in reading scientific charts and describing short videos; in a simulated task of planning for a robotic arm to place cream cheese into a bowl, Glimpse cost $0.035,

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  2. ZhidongxiSelected

    DeepSeek V4.1-Flash updated to V4.1-Flash-1017 and opens search and fetch APIs

    DeepSeek V4.1-Flash has been updated to version V4.1-Flash-1017; the official web, App and API have been updated in sync, and the model weights are available for download on HuggingFace and ModelScope. In the DeepSWE v1.1 test, the new model's max tier achieved a single-task pass rate of 77.0%, 2.8 percentage points higher than the previous version, and the average cost per task dropped from about 3.3 yuan to about 1.3 yuan. DeepSeek also opened to the public the Search and Fetch APIs of its self-developed search engine; both interfaces are priced at 5 yuan per thousand calls, and this part of access via server-side tool calls will be charged per call starting from 00:00 Beijing time on November 1.

    DeepSeek V4.1-Flash has been updated to version V4.1-Flash-1017; the official web, App and API have been updated in sync, and the model weights are available for download on HuggingFace and ModelScope. In the DeepSWE v1.1 test, the new model's max tier achieved a single-task pass rate of 77.0%, 2.8 percentage points higher than the previous version, and the average cost per task dropped from about 3.3 yuan to about 1.3 yuan. DeepSeek also opened to the public the Search and Fetch APIs of its sel

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    #hot-signal#Model releases#Open-source ecosystem#English text is being prepared.

Sunday

Wednesday

Friday

  1. TMTPost · AGISelected

    Google Releases Gemini 4 Carbon, Topping the Artificial Analysis Intelligence Index but Not Yet Publicly Available

    On October 28, Google released Gemini 4 Carbon, which topped the Artificial Analysis Intelligence Index v5.0 with a score of 59, surpassing Claude Opus 5.5's 58 and GPT-6 Astra's 57 to reclaim first place. The model is currently available only to a small number of cybersecurity defense personnel; when asked when ordinary developers and enterprises will be able to use it, officials responded only with "as soon as possible." On the GraphWalks ultra-long-context test, Carbon achieved 96.2% F1, far above GPT-6 Astra's 71.8% and Claude Opus 5.5's 66.8%; introductory pricing is $2 per million input tokens and $10 per million output tokens, the same as the previous-generation Argon.

    On October 28, Google released Gemini 4 Carbon, which topped the Artificial Analysis Intelligence Index v5.0 with a score of 59, surpassing Claude Opus 5.5's 58 and GPT-6 Astra's 57 to reclaim first place. The model is currently available only to a small number of cybersecurity defense personnel; when asked when ordinary developers and enterprises will be able to use it, officials responded only with "as soon as possible." On the GraphWalks ultra-long-context test, Carbon achieved 96.2% F1, far

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    #hot-signal#Model releases#Safety / alignment#Google
  2. cnBeta

    Google releases Gemini 4 Carbon, tops the Artificial Analysis leaderboard with 59 points

    Google released Gemini 4 Carbon, which scored 59 points on the Artificial Analysis Intelligence Index v5.0 leaderboard, surpassing Claude Opus 5.5's 58 points and GPT-6 Astra's 57 points. The model achieved 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, and Google says it can handle engineering problems in large codebases continuously for several days. The model this week is first being made available to some cybersecurity defenders, then expanded to trusted partners through the Fairwind Program, with no timeline yet for general users; initial pricing is $2 per million input tokens and $10 per million output tokens.

    Google released Gemini 4 Carbon, which scored 59 points on the Artificial Analysis Intelligence Index v5.0 leaderboard, surpassing Claude Opus 5.5's 58 points and GPT-6 Astra's 57 points. The model achieved 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, and Google says it can handle engineering problems in large codebases continuously for several days. The model this week is first being made available to some cybersecurity defenders, then expanded to trusted p

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    #hot-signal#Model releases#Google#Evaluations / benchmarks

Thursday

  1. Latent SpaceSelected

    Google DeepMind releases Gemini 4 Carbon, topping Artificial…

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1M maximum output, with input covering text, images, video, and speech, and output in text; Artificial Analysis lists a standard price of $4/$20 per million input/output tokens, plus a 50% launch discount.

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1

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    #newsletter#Model releases#Google#Safety / alignment

Saturday

  1. Latent SpaceSelected

    Moonshot AI releases Kimi K3.1 Pro: 2.8T total parameters, 104B activated parameters, weights scheduled to be opened on November 4

    Moonshot AI releases Kimi K3.1 Pro, a multimodal MoE model with 2.8T total parameters, 104B activated parameters, and a 1 million token context window. The Standard and Highspeed versions are now available on the Kimi website, App, Kimi Work, Kimi Code and API. The company says Highspeed offers 2–3x faster output at twice the price of the Standard version. Artificial Analysis ranks it fourth on the Intelligence Index with a score of 55, behind Opus 5.5's 58; on Arena's Code Arena WebDev it ranks 8th with 1692 points, up nine places from K3. Standard pricing is $2 per million tokens for input, $10 for output, and $0.2 for cached input, one-third lower than K3; the weights have not yet been released, and the company promises to open them on November 4.

    Moonshot AI releases Kimi K3.1 Pro, a multimodal MoE model with 2.8T total parameters, 104B activated parameters, and a 1 million token context window. The Standard and Highspeed versions are now available on the Kimi website, App, Kimi Work, Kimi Code and API. The company says Highspeed offers 2–3x faster output at twice the price of the Standard version. Artificial Analysis ranks it fourth on the Intelligence Index with a score of 55, behind Opus 5.5's 58; on Arena's Code Arena WebDev it ranks

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    #newsletter#Model releases#Open-source ecosystem#Agents

Monday

Tuesday

  1. Fireworks AI

    Meta's open-weight model Muse Spark Open launches on Fireworks: 816B parameters, 1M context

    Meta's open-weight model Muse Spark Open is available on Fireworks from day one of launch. It is an 816B-parameter MoE model that activates 42B parameters per token, with a 1M-token context window, targeting long-horizon coding and agentic tasks. Fireworks says it ranks first among 75 models on Vals AI's Harvey legal agent benchmark with 25.4%, nearly 4 times that of Claude Opus 5 (6.7%); on the Rogo Big Finance Bench it surpasses Claude Opus 5.5 at every difficulty level. Fireworks validated the weights with its own production stack, scoring 91.1% on AIME26, 89.7% on GPQA Diamond, and 84.3% on SWE-bench Verified, and reproduced consistent results with SGLang.

    Meta's open-weight model Muse Spark Open is available on Fireworks from day one of launch. It is an 816B-parameter MoE model that activates 42B parameters per token, with a 1M-token context window, targeting long-horizon coding and agentic tasks. Fireworks says it ranks first among 75 models on Vals AI's Harvey legal agent benchmark with 25.4%, nearly 4 times that of Claude Opus 5 (6.7%); on the Rogo Big Finance Bench it surpasses Claude Opus 5.5 at every difficulty level. Fireworks validated th

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    #editorial#Product updates#Model releases#English text is being prepared.

Thursday