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Sunday21 items

  1. QbitAIModel releases
    AI score84

    Google Releases Gemini 4 Argon, Limited-Time Half-Price API

    Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, about 39% lower than Astra. Google says that on an ADK project it worked unattended continuously for 11 hours, proposed six optimization plans involving 32 files, and ran 16,892 tests, two of which were merged, reducing long-session memory preparation overhead by about 40%.

    #Model releases#Google#Multimodal

  2. shao_mengModel releases
    AI score60

    English translation is being prepared.

    Quoted postDeepSeek · @deepseek_ai

    🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4

    Same story · 24 reports

    #Model releases#Agents#DeepSeek

  3. Tianyi CuiModel releases
    AI score74

    DeepSeek-V4.1-Flash-1017 Released, Requires Upgrading to DeepSeek Harness 0.2.1-rc.1

    DeepSeek has released DeepSeek-V4.1-Flash-1017, stating that it delivers stronger benchmark performance, faster task completion, and shorter outputs than the previous version, representing a Pareto improvement in performance and cost, and it is now live on the official website, App, and API. The model has been optimized for DeepSeek Harness, Tencent CodeBuddy, WorkBuddy, and others; using DeepSeek Harness requires upgrading to v0.2.1-rc.1 or a later version.

    Quoted postDeepSeek · @deepseek_ai

    🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4

    Same story · 24 reports

    #Product updates#DeepSeek#Model releases

  4. Testing CatalogModel releases
    AI score80

    DeepSeek Releases Open-Weight Model DeepSeek-V4.1-Flash-1017

    DeepSeek releases the open-weight model DeepSeek-V4.1-Flash-1017, scoring 77% on the DeepSWE 1.1 benchmark, surpassing models such as GLM-5.3, Kimi K3, GPT-5.6 Sol, and Opus 5. The model is now available on DeepSeek Chat, the API, and HuggingFace, and the publisher says its performance and cost both improved over the previous version.

    Quoted postDeepSeek · @deepseek_ai

    🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4

    Same story · 24 reports

    #Model releases#Open-source ecosystem#DeepSeek

  6. Nathan LambertModel releases
    AI score67

    DeepSeek-V4.1-Flash-1017 released, with simultaneous improvements in benchmark performance and cost

    DeepSeek has released DeepSeek-V4.1-Flash-1017, claiming stronger benchmark performance, faster task completion, and shorter outputs, achieving a Pareto improvement in performance and cost; it is now live on the official website, App, and API. This version has been optimized for DeepSeek Harness, Tencent CodeBuddy, WorkBuddy, and others, and requires upgrading to DeepSeek Harness v0.2.1-rc.1 or later for the best experience. Nathan Lambert thinks its naming approach (a minor version number plus a date tag) is quite absurd, but the benchmark gains are large, and with built-in vision capability it may be stronger than GLM 5.3.

    Quoted postDeepSeek · @deepseek_ai

    🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4

    Same story · 24 reports

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

Saturday10 items

  2. arenaModel releases
    AI score67

    English translation is being prepared.

    Quoted postAI at Meta · @AIatMeta

    Today we’re releasing Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning. Key Model Specs: → 816B total / 42B active parameters → 1M token context window → Natively multimodal across text, image, video, audio

    #Evaluations / benchmarks#Open-source ecosystem#Meta

  3. Clément DelangueModel releases
    AI score58

    Perplexity Open-Sources pplx-decider-v1.2 and Flash Multimodal Decision Models

    Perplexity has released its next-generation open-weight multimodal decision models, comprising two sizes, pplx-decider-v1.2 and pplx-decider-flash-v1.2, with improvements in both text and vision scores, inference up to 5x faster, and all questions in a single request completed in one pass. Hugging Face co-founder Clément Delangue reposted the news and noted that the weights have been published on Hugging Face. Perplexity says the flash version is the top-ranked 4B model on the Decision Index.

    Quoted postPerplexity Developers · @perplexitydevs

    Our next generation of open weights multimodal decision models comes in two sizes, pplx-decider-v1.2 and pplx-decider-flash-v1.2. Text and vision scores improve. Inference is up to 5x faster: all questions in a request run in one pass. Flash is the top 4B on the Decision Index. https://t.co/Zb1MN36aFi

    #Industry news#Open-source ecosystem#Hugging Face

  5. Aravind SrinivasModel releases
    AI score62

    Perplexity Open-Sources Two Decision Models: pplx-decider-v1.2 and flash-v1.2

    Perplexity has open-sourced two decision models: pplx-decider-flash-v1.2 has 4B parameters and costs 1 cent per million tokens, making it the strongest 4B model on the HF Decision Index; pplx-decider-v1.2 has 27B parameters and costs 2 cents per million tokens, ranking 2nd on the overall HF Decision Index leaderboard. Both are now live on the Perplexity Decisions API and offer open weights on Hugging Face. Perplexity Developers says this generation of open-weight multimodal decision models improves on both text and vision scores, delivers inference up to 5x faster, and completes all questions in a request in a single forward pass.

    Quoted postPerplexity Developers · @perplexitydevs

    Our next generation of open weights multimodal decision models comes in two sizes, pplx-decider-v1.2 and pplx-decider-flash-v1.2. Text and vision scores improve. Inference is up to 5x faster: all questions in a request run in one pass. Flash is the top 4B on the Decision Index. https://t.co/Zb1MN36aFi

    #Model releases#Open-source ecosystem#Hugging Face

  6. testingcatalogModel releases
    AI score70

    English translation is being prepared.

    Quoted postAndrew M. Dai · @AndrewDai

    Spent years watching models ace a single image and completely whiff on anything that moves or changes angle. Today we’re fixing that. Try Glimpse now, our first visual thinking model with competitive frontier performance compared to Astra on key public visual reasoning benchmarks.

    Same story · 3 reports

    #Model releases#Multimodal#Video

  7. arenaModel releases
    AI score52

    English translation is being prepared.

    Quoted postArena.ai · @arena

    Exciting news: Beam-1.0-501B-A23B by @Reflection_AI just landed #12 among open weight models in Agent Arena with -3.67% Net Improvement, and #22 among open in Code Arena: WebDev with 1438 pts. It’s also fully open under Apache 2.0. On the Agent Arena leaderboard, Beam 1.0 is the top-ranked US model among open models, landing at #12. That puts it ahead of Hy3, MiMo V2.5 Pro and MiniMax M3. Its margin of error is wide (±3.84% on Net Improvement), so it’s statistically closer to the two Qwen3.8 models just above it than its rank suggests. On Code Arena: WebDev, 24 of the top 25 open models come from Chinese labs. The one exception is Reflection’s Beam 1.0 (Apache 2.0). It ranks #22 among open models, which makes it the top US open model on the board, just ahead of Kimi K2.5 Thinking and GLM-5. Congrats to the @Reflection_AI team on this solid open weights release!

    Same story · 2 reports

    #Evaluations / benchmarks#Open-source ecosystem#Agents

  9. CNETModel releases
    AI score75

    Meta and Apple Partner to Release Open-Weight Model Muse Spark Open

    Meta has released the open-weight model Muse Spark Open and worked with Apple's hardware team to enable it to run efficiently on the M5 Mac Studio Ultra. The model has 42 billion active parameters, a 1 million token context window, and multimodal capabilities. Meta says it performs well on agentic and coding tasks, and the weights have been made public on HuggingFace under Meta's Muse Model license. Running the model on an Apple computer requires two Mac Studios equipped with the M5 Ultra, each starting at $5,499.

    Same story · 33 reports

    #Model releases#Open-source ecosystem#Agents

  10. TechCrunch AIModel releases
    AI score57

    Elorian Releases Its First Model Glimpse, Using a Visual Draft Space for Image Reasoning

    Elorian has released its first model, Glimpse, opening the API as a research preview, with a waitlist for the chat interface. During reasoning, the model can crop image regions, extract video frames, or run code to measure and compare what it sees, which Elorian calls a visual draft space. Glimpse is priced at $0.60 per million input tokens and $3 per million output tokens, and according to Elorian's evaluations it surpasses GPT-6 Astra on scientific chart reasoning and short video description. The company says the model was trained on several hundred GPUs, a scale notably smaller than the frontier systems it benchmarks against, and it initially targets enterprises with large amounts of video, such as robotics, research laboratories, and media and creative firms.

    Same story · 3 reports

    #Model releases#Multimodal#Reasoning