Nathan Lambert commented that people underestimate how much money can still be invested in the sovereign AI sector. This tweet cites Giotto AI's announcement of the release of two European sovereign AI models, Giotto Alto and Giotto Solo, of which Alto is aimed at advanced reasoning, is freely open, and is hosted on European cloud infrastructure, while Solo can run on a single GPU.
Ant Group's AntLingAGI has released Ling 3.1 Flash 1019, an updated version of Ling 3.1 Flash, scoring 44 on the Artificial Analysis Intelligence Index v4.3, up from 41 for the previous generation. The model is a reasoning model with 560B total parameters and 25B activated parameters, supports a 1M token context window, is released under the MIT license, is available as open weights on Hugging Face, and can be accessed via InclusionAI's first-party API. In terms of agentic capabilities, AA-Briefcase v1.1's Elo rose from 1397 to 1521, GDPval-AA v2.1 rose from 1617 to 1653, and AutomationBench-AA rose from 62% to 68%; Humanity's Last Exam rose from 39% to 43%, and CritPt rose from 18% to 26%. Output tokens per task increased to 145k, up from 103k for the previous generation, with a cost of $1.49 per task and pricing of $0.30 per 1M input tokens and $0.90 per 1M output tokens.
Ant Group's AntLingAGI has released Ling 3.1 Flash 1019, an updated version of Ling 3.1 Flash, scoring 44 on the Artificial Analysis Intelligence Index v4.3, up from 41 for the previous generation. The model is a reasoning model with 560B total parameters and 25B activated parameters, supports a 1M token context window, is released under the MIT license, is available as open weights on Hugging Face, and can be accessed via InclusionAI's first-party API. In terms of agentic capabilities, AA-Brief
NVIDIA announced a $3 billion investment in Meta's equity offering, and the two companies will expand their collaboration on the personal agent product Muse and the Muse series of models to improve model inference and training performance. The investment is part of Meta's $95 billion fundraising plan, and AMD and Broadcom have also expressed interest in investing. Meta expects full-year capital expenditure of $135 billion to $145 billion and will consider adopting NVIDIA's OpenShell secure agent reference architecture and expanding deployments of infrastructure including Vera Rubin, Vera CPU, and Spectrum-X networking.
NVIDIA announced a $3 billion investment in Meta's equity offering, and the two companies will expand their collaboration on the personal agent product Muse and the Muse series of models to improve model inference and training performance. The investment is part of Meta's $95 billion fundraising plan, and AMD and Broadcom have also expressed interest in investing. Meta expects full-year capital expenditure of $135 billion to $145 billion and will consider adopting NVIDIA's OpenShell secure agent
Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world model architecture. It has opened beta applications to Google AI Ultra users and is also available in the Gemini API and Google AI Studio.
Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world mo
Oracle and Google announced at Oracle AI World that Google TPU will be offered through Oracle Cloud Infrastructure (OCI). Oracle says OCI is the first hyperscale cloud platform outside Google to offer Google TPU, with availability planned within the 2027 calendar year. OCI will handle power, cooling, and data center networking, supporting large model training, post-training (including dense and MoE models), as well as production inference for inference, agent, and long-context scenarios. The two sides also introduced the eighth-generation TPU, with the TPU 8t training version and TPU 8i inference version, among which the TPU 8t delivers nearly 3 times the compute of a single pod compared with the previous generation.
Oracle and Google announced at Oracle AI World that Google TPU will be offered through Oracle Cloud Infrastructure (OCI). Oracle says OCI is the first hyperscale cloud platform outside Google to offer Google TPU, with availability planned within the 2027 calendar year. OCI will handle power, cooling, and data center networking, supporting large model training, post-training (including dense and MoE models), as well as production inference for inference, agent, and long-context scenarios. The two
On October 27, Liquid AI released the LFM3 series. All six 2B-parameter-class open-weight models branch from the same LFM3-1.7B-Base, covering text, vision, audio, omni-modal, and decision models. LFM3-1.7B has 1.73B parameters, a 256K token context, supports 16 languages, and adopts a Tri-Hybrid architecture with 13 layers of gated short convolutions, 5 layers of sliding-window attention, and 6 layers of global attention. It is available under the LFM Open License v1.0 on Hugging Face, the Liquid AI Playground, and via API. The company claims that LFM3-1.7B surpasses LFM2.5-2.6B with 35% fewer parameters and occupies about 1 GB of memory at 4-bit precision, but the model card states that it is not suitable for agentic coding or complex multi-step reasoning.
On October 27, Liquid AI released the LFM3 series. All six 2B-parameter-class open-weight models branch from the same LFM3-1.7B-Base, covering text, vision, audio, omni-modal, and decision models. LFM3-1.7B has 1.73B parameters, a 256K token context, supports 16 languages, and adopts a Tri-Hybrid architecture with 13 layers of gated short convolutions, 5 layers of sliding-window attention, and 6 layers of global attention. It is available under the LFM Open License v1.0 on Hugging Face, the Liqu
Oracle announced plans to offer Google TPU accelerators in its own public cloud; this is the first time Google has supplied chips to another hyperscale cloud provider, with deployment set to begin next year and gradually scale up. Oracle will also deploy Cerebras' wafer-scale accelerators and OpenAI's Jalapeño inference chips, and use OpenAI models to power new cloud services. The two sides are also launching AI Workspace, which lets ChatGPT perform tasks on users' behalf within Oracle applications, along with App Composer, AI Security Mesh, and the Oracle AI SMB Bundle for small businesses.
Oracle announced plans to offer Google TPU accelerators in its own public cloud; this is the first time Google has supplied chips to another hyperscale cloud provider, with deployment set to begin next year and gradually scale up. Oracle will also deploy Cerebras' wafer-scale accelerators and OpenAI's Jalapeño inference chips, and use OpenAI models to power new cloud services. The two sides are also launching AI Workspace, which lets ChatGPT perform tasks on users' behalf within Oracle applicati
Ai2 released the "Old Ideas, Novel Problems" study and a companion benchmark, testing the reliability of six models—GPT-5.1, GPT-5.2, GPT-5.4, Claude Sonnet 4.5, Claude Opus 4.5, and Claude Opus 4.6—at judging the novelty of research ideas. The results show that small changes to the evaluation setup produce drastic differences: after switching GPT-5.4 to a simpler prompt on the Human+Generated data, its accuracy dropped from 93.5% to 40.9%, below chance level. The study also found that retrieval and additional reasoning do not reliably improve judgment quality; two purpose-built novelty evaluation systems performed worse than a simple Claude Opus 4.6 prompt baseline and cost more.
Ai2 released the "Old Ideas, Novel Problems" study and a companion benchmark, testing the reliability of six models—GPT-5.1, GPT-5.2, GPT-5.4, Claude Sonnet 4.5, Claude Opus 4.5, and Claude Opus 4.6—at judging the novelty of research ideas. The results show that small changes to the evaluation setup produce drastic differences: after switching GPT-5.4 to a simpler prompt on the Human+Generated data, its accuracy dropped from 93.5% to 40.9%, below chance level. The study also found that retrieval
NVIDIA and Meta announced an expanded collaboration around Muse and the Muse family of models to improve inference and training performance, with NVIDIA investing $3 billion in Meta equity. Meta plans to expand its deployment of NVIDIA infrastructure, including the Vera Rubin platform and Vera CPU for next-generation AI agents, and to deploy Spectrum-X Ethernet networking and BlueField-4. The two sides will also explore collaboration on secure AI agent deployment and behavior monitoring on NVIDIA's OpenShell reference architecture.
NVIDIA and Meta announced an expanded collaboration around Muse and the Muse family of models to improve inference and training performance, with NVIDIA investing $3 billion in Meta equity. Meta plans to expand its deployment of NVIDIA infrastructure, including the Vera Rubin platform and Vera CPU for next-generation AI agents, and to deploy Spectrum-X Ethernet networking and BlueField-4. The two sides will also explore collaboration on secure AI agent deployment and behavior monitoring on NVIDI
LiteRT in Google Play services receives its biggest upgrade: GPU inference based on ML Drift is about 1.4x faster than the old GPU delegate and is provided through the new CompiledModel API. After switching to this runtime, app size shrinks by about 8 MB, because the runtime is distributed uniformly with Play services and is no longer packaged into the APK; currently more than 100,000 Android apps already bundle LiteRT or TensorFlow Lite. This solution supports Android 7 and above, Wear OS 4+, and Android Automotive OS (Android 11+); NPU support is still in development.
LiteRT in Google Play services receives its biggest upgrade: GPU inference based on ML Drift is about 1.4x faster than the old GPU delegate and is provided through the new CompiledModel API. After switching to this runtime, app size shrinks by about 8 MB, because the runtime is distributed uniformly with Play services and is no longer packaged into the APK; currently more than 100,000 Android apps already bundle LiteRT or TensorFlow Lite. This solution supports Android 7 and above, Wear OS 4+, a
Microsoft AI has released the image editing model MAI-Image-2.7-Preview, which ranks second on Artificial Analysis's AA-Image-Editing v2.1 leaderboard, behind only OpenAI's GPT Image 2.5 Sunburst (max). The model outperforms MAI-Image-2.6 on all 7 evaluated editing actions, with the largest improvement in composition and framing (+57 Elo), followed by text or symbol editing +49 and scene and style editing +48, and it ranks first in 4 categories: scene and style editing, text or symbol editing, reasoning-based editing, and enhancement and restoration. The model currently offers image editing only in the MAI Playground, with text-to-image functionality said to be coming soon.
Microsoft AI has released the image editing model MAI-Image-2.7-Preview, which ranks second on Artificial Analysis's AA-Image-Editing v2.1 leaderboard, behind only OpenAI's GPT Image 2.5 Sunburst (max). The model outperforms MAI-Image-2.6 on all 7 evaluated editing actions, with the largest improvement in composition and framing (+57 Elo), followed by text or symbol editing +49 and scene and style editing +48, and it ranks first in 4 categories: scene and style editing, text or symbol editing, r
Google has released its latest model, Gemini 4 Argon, saying it is aimed at complex real-world tasks and can perform reasoning, coding, and coordinate tools. The company provided 8 examples, including writing 5,000 lines of mathematical code from scratch with zero source material to render a 3D sunlit library, and, in Antigravity, processing more than 80,000 raw files from a NASA Mars mission and generating executive briefing slides.
Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the camera, changing the weather, or introducing new characters, and each world also generates ambient sound, music, and interactive dialogue on the fly.
Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the cam
Ant inclusionAI has open-sourced Zooming without Zooming v2 (ZwZ2), trained on Qwen3.5-4B/9B and Qwen3.6-27B using GRPO reinforcement learning, with training data consisting of 20.4K multi-region VQA samples validated across models. The models are trained on full images and require no zooming tools at inference time, and can be transferred to perception, spatial reasoning, long-context understanding, and multimodal agent tasks. The code, data synthesis, and evaluation pipeline are all released under the Apache 2.0 license.
Ant inclusionAI has open-sourced Zooming without Zooming v2 (ZwZ2), trained on Qwen3.5-4B/9B and Qwen3.6-27B using GRPO reinforcement learning, with training data consisting of 20.4K multi-region VQA samples validated across models. The models are trained on full images and require no zooming tools at inference time, and can be transferred to perception, spatial reasoning, long-context understanding, and multimodal agent tasks. The code, data synthesis, and evaluation pipeline are all released u
OpenAI has released a new model, GPT-6.1 Terra, with standard API input pricing reduced to $1 per million tokens and output at $5, a 50% decrease compared with GPT-5.6 Terra. The model focuses on visual understanding and computer operation, scoring 50.3% at the highest reasoning effort on the Terminal-Bench 4.0 coding benchmark, up from 21.5% for the previous generation. OpenAI says the most complex coding tasks are still better suited to GPT-6.1 Sol or GPT-6 Astra.
On October 26 local time, on the same day Anthropic submitted its IPO registration filing to the SEC, OpenAI released its new model GPT-6.1 Terra, with standard API prices cut by 50% compared with the previous generation. The model focuses on visual understanding and computer operation, with standard API pricing at $1 per million input tokens, $5 for output, and $0.05 for cached input; on the Terminal-Bench 4.0 coding benchmark, it scored 50.3% at the highest reasoning effort, compared with 21.5% for the previous generation. OpenAI said Terra has approached flagship-model levels on some tasks, but the most complex coding tasks are still better suited to GPT-6.1 Sol or GPT-6 Astra.
On October 26 local time, on the same day Anthropic submitted its IPO registration filing to the SEC, OpenAI released its new model GPT-6.1 Terra, with standard API prices cut by 50% compared with the previous generation. The model focuses on visual understanding and computer operation, with standard API pricing at $1 per million input tokens, $5 for output, and $0.05 for cached input; on the Terminal-Bench 4.0 coding benchmark, it scored 50.3% at the highest reasoning effort, compared with 21.5
OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, down 50% and about 58% respectively from the previous generation, and half the price of GPT-6.1 Sol. OpenAI says its task completion rate on Terminal-Bench 4.0 rose from 21.5% to 50.3%, and its error rate at the highest reasoning level on difficult factual tests dropped to 4.3%. Third-party organization Artificial Analysis measured an intelligence index of 48 points, lower than Sol's 52 points and Claude Opus 5.5's 58 points, but the average cost per task fell from $1.40 to $0.40. The model is now available via API, and Plus, Pro, Enterprise, and Edu users can use it in ChatGPT Work and Codex; ordinary Chat conversations are not yet supported.
OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, down 50% and about 58% respectively from the previous generation, and half the price of GPT-6.1 Sol. OpenAI says its task completion rate on Terminal-Bench 4.0 rose from 21.5% to 50.3%, and its error rate at the highest reasoning level on difficult factual tests dropped to 4.3%. Third-party organization Artificial Analysis measured an intelligence index of 48 points, lower than So
OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, representing a 50% and approximately 58% decrease in input and output prices respectively compared to the previous generation, and only half that of GPT-6.1 Sol. The company claims its task completion rate on Terminal-Bench 4.0 increased from 21.5% to 50.3%, and it scored 60.0% on Agents' Last Exam, close to Claude Opus 5.5's 63.2%. Artificial Analysis measured an intelligence index of 48 at the highest reasoning tier, lower than GPT-6.1 Sol's 52 and Claude Opus 5.5's 58, but the average cost per task dropped from $1.40 to $0.40. Terra is now available via API, and Plus, Pro, Enterprise, and Edu users can use it in ChatGPT Work and Codex; it is not yet supported in regular Chat conversations.
OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, representing a 50% and approximately 58% decrease in input and output prices respectively compared to the previous generation, and only half that of GPT-6.1 Sol. The company claims its task completion rate on Terminal-Bench 4.0 increased from 21.5% to 50.3%, and it scored 60.0% on Agents' Last Exam, close to Claude Opus 5.5's 63.2%. Artificial Analysis measured an intelligence ind
OpenAI has released GPT-6.1 Terra, which combines visual reasoning, computer use, and coding capabilities. Its API pricing is $1 per million input tokens, $0.05 per million cached input tokens, and $5 per million output tokens, 50% lower than GPT-5.6 Terra and GPT-6.1 Sol. Starting October 27, the model is available to Plus, Pro, Enterprise, and Edu users of ChatGPT Work and Codex, and developers can call it via the API as gpt-6.1-terra. On Terminal-Bench 4.0, it solves 50.3% of tasks at maximum reasoning effort, compared with the 21.5% score published for GPT-5.6 Terra; on an internal induced-error benchmark, the error rate at low reasoning effort dropped from 53.6% to 16.7%. The release comes as OpenAI resumes frontier model training after an 11-day pause over safety concerns.
OpenAI has released GPT-6.1 Terra, which combines visual reasoning, computer use, and coding capabilities. Its API pricing is $1 per million input tokens, $0.05 per million cached input tokens, and $5 per million output tokens, 50% lower than GPT-5.6 Terra and GPT-6.1 Sol. Starting October 27, the model is available to Plus, Pro, Enterprise, and Edu users of ChatGPT Work and Codex, and developers can call it via the API as gpt-6.1-terra. On Terminal-Bench 4.0, it solves 50.3% of tasks at maximum
OpenAI released GPT-6.1 Terra, focused on visual reasoning, computer operation, and writing. It is now available to Plus, Pro, Enterprise, and Edu users of ChatGPT Work and Codex, as well as via API. The standard API charges $1, $0.05, and $5 per million input, cached input, and output tokens respectively, 50% lower than GPT-5.6 Terra and GPT-6.1 Sol. Anthropic has submitted an S-1 to the SEC to list on Nasdaq under the ticker "ANT"; first-half revenue was $16.286 billion, with net loss widening to $80.748 billion. Apple released the iPad mini (A20 Pro) the same day, starting at 128GB, with the Wi-Fi model starting at 5,499 yuan, on sale November 6.
OpenAI released GPT-6.1 Terra, focused on visual reasoning, computer operation, and writing. It is now available to Plus, Pro, Enterprise, and Edu users of ChatGPT Work and Codex, as well as via API. The standard API charges $1, $0.05, and $5 per million input, cached input, and output tokens respectively, 50% lower than GPT-5.6 Terra and GPT-6.1 Sol. Anthropic has submitted an S-1 to the SEC to list on Nasdaq under the ticker "ANT"; first-half revenue was $16.286 billion, with net loss widening
