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Thursday

  1. The DecoderSelected

    Google DeepMind releases Gemini 4 Carbon, just two weeks after Argon

    Google DeepMind launched Gemini 4 Carbon two weeks after the release of Argon. The model scored 59 on the Artificial Analysis Intelligence Index v5.0, higher than Argon's 50, ranking first. Carbon is designed for long-horizon engineering tasks, rose to 1769 points and fourth place on WebDev Arena, and reduced the attack success rate from 0.7% to 0.0% on the Gray Swan indirect prompt injection benchmark. The model is first being made available to select cybersecurity experts, priced at $2 per million input tokens and $10 per million output tokens, in line with Argon's introductory pricing.

    Google DeepMind launched Gemini 4 Carbon two weeks after the release of Argon. The model scored 59 on the Artificial Analysis Intelligence Index v5.0, higher than Argon's 50, ranking first. Carbon is designed for long-horizon engineering tasks, rose to 1769 points and fourth place on WebDev Arena, and reduced the attack success rate from 0.7% to 0.0% on the Gray Swan indirect prompt injection benchmark. The model is first being made available to select cybersecurity experts, priced at $2 per mil

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    #ai-vertical#Model releases#Google#Reasoning
  2. The Decoder

    Mistral Releases Mistral Large 4 Weights: Coding Ability Leads Open-Source Models but Overall Trails Chinese Models

    Mistral has released the weights of Mistral Large 4 on Hugging Face. The model, nicknamed Le Chonk, has approximately 1 trillion parameters with 52 billion activated per step, and supports text and image inputs. On Terminal-Bench 4.0, its score rose from 28% in the preview version to 41%, slightly above GLM-5.3's 40%, but on the new version of the Artificial Analysis Intelligence Index it scored only 26 points, below the 32 points of DeepSeek V4.1 Flash and GLM-5.3. API pricing is $0.70 per million input tokens and $2.10 per million output tokens, under a modified MIT license; using it as a commercial cloud service requires separate authorization.

    Mistral has released the weights of Mistral Large 4 on Hugging Face. The model, nicknamed Le Chonk, has approximately 1 trillion parameters with 52 billion activated per step, and supports text and image inputs. On Terminal-Bench 4.0, its score rose from 28% in the preview version to 41%, slightly above GLM-5.3's 40%, but on the new version of the Artificial Analysis Intelligence Index it scored only 26 points, below the 32 points of DeepSeek V4.1 Flash and GLM-5.3. API pricing is $0.70 per mill

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    #ai-vertical#Model releases#Open-source ecosystem#English text is being prepared.
  3. 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
  4. t3n

    Mistral Large 4 weights go live on Hugging Face; the company says it leads on CyberGym-E2E and…

    After a three-week preview, Mistral AI has released the weights of Mistral Large 4 on Hugging Face. This multimodal model was trained on 3,800 Nvidia accelerators and has a parameter count of one trillion, and it is currently still difficult to run on a gaming PC or a single GPU. Mistral says it leads GLM-5.3 and Kimi K3 on the cybersecurity benchmark CyberGym-E2E, and is on par with GLM-5.3 on the agentic coding benchmark Terminal Bench 4.0, but there is no independent evaluation yet; preview pricing is $1.4 per million input tokens and $4.2 per million output tokens.

    After a three-week preview, Mistral AI has released the weights of Mistral Large 4 on Hugging Face. This multimodal model was trained on 3,800 Nvidia accelerators and has a parameter count of one trillion, and it is currently still difficult to run on a gaming PC or a single GPU. Mistral says it leads GLM-5.3 and Kimi K3 on the cybersecurity benchmark CyberGym-E2E, and is on par with GLM-5.3 on the agentic coding benchmark Terminal Bench 4.0, but there is no independent evaluation yet; preview p

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    #hot-signal#Model releases#Open-source ecosystem#Hugging Face
  5. QbitAISelected

    Google Releases Gemini 4 Carbon, Surpassing Claude Opus 5.5 on Multiple Benchmarks

    Google has released its new flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index 5.0 with a score of 59, surpassing Claude Opus 5.5 and GPT-6 Astra. It scored 65.2% on Terminal-Bench 4.0, 96.2% on GraphWalks for 256k to 1M context, and 88.2% on SEC-bench Pro vulnerability discovery. Initial pricing is $2 per million tokens for input and $10 per million tokens for output, with cached input as low as $0.2; because of its vulnerability discovery and exploitation capabilities, it will first be made available to select cybersecurity defenders.

    Google has released its new flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index 5.0 with a score of 59, surpassing Claude Opus 5.5 and GPT-6 Astra. It scored 65.2% on Terminal-Bench 4.0, 96.2% on GraphWalks for 256k to 1M context, and 88.2% on SEC-bench Pro vulnerability discovery. Initial pricing is $2 per million tokens for input and $10 per million tokens for output, with cached input as low as $0.2; because of its vulnerability discovery and exploitation cap

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    #chinese#Model releases#Google#DeepMind
  6. QbitAI

    Diffusion Intelligence releases Clover-35B-A3B-Preview, a 35-billion-parameter diffusion language model

    Diffusion Intelligence releases the diffusion language model Clover-35B-A3B-Preview, which uses a MoE architecture with 35 billion total parameters and about 3 billion activated per token, and supports a thinking mode. On the 49 tasks of the web Agent benchmark WindTunnel, its median execution time was 1.52 seconds, lower than the 3.21 seconds of the Jev + Mercury 2.5 combination, with success rates of 98.6% and 95.9% respectively. On code benchmarks, it scored 73.6 on SWE-bench Verified and 51.7 on Terminal-Bench 2.1, and the team said it will subsequently launch a multimodal version and advance on-device adaptation.

    Diffusion Intelligence releases the diffusion language model Clover-35B-A3B-Preview, which uses a MoE architecture with 35 billion total parameters and about 3 billion activated per token, and supports a thinking mode. On the 49 tasks of the web Agent benchmark WindTunnel, its median execution time was 1.52 seconds, lower than the 3.21 seconds of the Jev + Mercury 2.5 combination, with success rates of 98.6% and 95.9% respectively. On code benchmarks, it scored 73.6 on SWE-bench Verified and 51.

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    #chinese#Model releases#Agents#English text is being prepared.
  7. MarkTechPost

    Block Releases Dessa, a Fully Duplex Speech Model Trained Purely on Speech

    Block's AI research lab has released Dessa, a full-duplex speech model, opening a waitlist in the form of a research preview. It is trained only on human voice conversation audio, without using text or pretrained models. The model can run locally on a MacBook Pro M4 Max or higher configuration, faster than real time; training used one NVIDIA GB200 NVL72 (72 GPUs). No benchmark scores, parameter count, weights, paper, or API have been published so far.

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    #ai-vertical#Model releases#Speech#Open-source ecosystem
  8. Leiphone.com

    Leiphone.com's In-Depth Breakdown of Google DeepMind's World Model Genie 4

    Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network architecture or scheduling implementation of Genie 4.

    Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network archite

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    #hot-signal#Model releases#Multimodal#Agents

Friday

  1. Ant Group inclusionAI: New GitHub Repository

    Ant Group's inclusionAI Open-Sources 2B Visual Forensics Model DefakerOne2

    Ant Group's GuangJian team has open-sourced DefakerOne2 on GitHub, a 2B-parameter unified visual forensics model built on the Qwen3.5-2B multimodal backbone, covering AI-generated content, DeepFake faces, document tampering, natural image tampering, face and ID anti-counterfeiting, and AI-generated video detection. The model was trained on approximately 50 million samples, employs a three-stage Tide-Style Tuning process from LoRA to full parameters and back to LoRA, and uses entropy-based test-time routing to select between the video and frame pathways. The team claims that it achieves SOTA on 40 of 53 detection benchmarks and on 11 of 14 localization benchmarks, and that the weights and the RRVBench benchmark have been released on ModelScope.

    GitHub

    Ant Group's GuangJian team has open-sourced DefakerOne2 on GitHub, a 2B-parameter unified visual forensics model built on the Qwen3.5-2B multimodal backbone, covering AI-generated content, DeepFake faces, document tampering, natural image tampering, face and ID anti-counterfeiting, and AI-generated video detection. The model was trained on approximately 50 million samples, employs a three-stage Tide-Style Tuning process from LoRA to full parameters and back to LoRA, and uses entropy-based test-t

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    #engineering#Model releases#Open-source ecosystem#Multimodal
  2. Baseten Engineering BlogSelected

    Baseten releases decision model joey-1, with P50 latency of 20ms and $0.01 per million tokens

    Baseten's Base Labs has released joey-1, a 2B decision model that directly outputs a single-token label and calibrated confidence, with a P50 end-to-end latency of 20ms, about 2.5 times faster than elephant-1 (49ms), at a price of $0.01 per million tokens, one-tenth that of mammoth-1. joey-1 is post-trained from Qwen3.5-2B and shares the same data recipe and API with elephant-1 and mammoth-1, so switching requires changing only one line. The model is now available on Baseten Model APIs, with zero data retention by default, and its weights are open-sourced on Hugging Face; Model APIs supports a 16k context window, while dedicated deployments can unlock a 262k context window and support fine-tuned weights.

    joey-1

    Baseten's Base Labs has released joey-1, a 2B decision model that directly outputs a single-token label and calibrated confidence, with a P50 end-to-end latency of 20ms, about 2.5 times faster than elephant-1 (49ms), at a price of $0.01 per million tokens, one-tenth that of mammoth-1. joey-1 is post-trained from Qwen3.5-2B and shares the same data recipe and API with elephant-1 and mammoth-1, so switching requires changing only one line. The model is now available on Baseten Model APIs, with zer

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    #editorial#Model releases#Reasoning#Open-source ecosystem
  3. 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

Wednesday

  1. Hugging FaceSelected

    NVIDIA Releases Nemotron 3.5 Transcribe and Granary v2 Data Pipeline

    NVIDIA has released the open-weight model Nemotron 3.5 Transcribe on Hugging Face and ModelScope, integrating transcription, speaker diarization, translation, and audio question answering into a single checkpoint. It supports transcription in 40 languages, translation between 31 languages and English, and speaker labeling in 13 languages, can process recordings up to 1 hour long, and can label up to 8 speakers. The model ranks first among open-weight models on the English leaderboard of the Hugging Face Open ASR Leaderboard with an average WER of 5.33%, and achieves 2.8% AA-WER on Artificial Analysis with approximately 4B activated parameters. The simultaneously released Granary v2 covers 48 languages and 463,062 hours of speech data, and the accompanying NeMo Speech fine-tuning recipe reduced WER on held-out speakers from 22.44% to 12.17% in a medical case.

    NVIDIA has released the open-weight model Nemotron 3.5 Transcribe on Hugging Face and ModelScope, integrating transcription, speaker diarization, translation, and audio question answering into a single checkpoint. It supports transcription in 40 languages, translation between 31 languages and English, and speaker labeling in 13 languages, can process recordings up to 1 hour long, and can label up to 8 speakers. The model ranks first among open-weight models on the English leaderboard of the Hugg

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    #lab#Model releases#Speech#Open-source ecosystem
  2. MarkTechPost

    Google DeepMind Releases Genie 4 Real-Time World Model with Native Audio Generation

    Google DeepMind has released the Genie 4 world model as a research preview to trusted testers; it can generate explorable worlds in real time from text and image prompts, and natively generate ambient sound, music, and character dialogue. The model introduces Gemini 3.8 Flash as a planner within the simulation loop, responsible for breaking down goals, inspecting frames, and replanning, which DeepMind calls an early step toward hybrid world models. Genie 4 is hosted only on Google's platform and will later be opened to AI Ultra users and Gemini API partners; all video and audio carry SynthID watermarks.

    Google DeepMind has released the Genie 4 world model as a research preview to trusted testers; it can generate explorable worlds in real time from text and image prompts, and natively generate ambient sound, music, and character dialogue. The model introduces Gemini 3.8 Flash as a planner within the simulation loop, responsible for breaking down goals, inspecting frames, and replanning, which DeepMind calls an early step toward hybrid world models. Genie 4 is hosted only on Google's platform and

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    #ai-vertical#Model releases#Multimodal#Agents
  3. SiliconANGLE

    Google previews Genie 4 world model, which can generate 3D environments with audio

    Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time interaction. Internally, the model calls Gemini Omni to ensure visual realism and Gemini 3.8 Flash to maintain inter-frame consistency. It is currently being tested with a small number of early users and will later be offered through the Google AI Ultra subscription, the Gemini API, and Google AI Studio.

    Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time inter

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    #hot-signal#Model releases#Multimodal#Google
  4. Hugging FaceSelected

    Liquid AI Releases the LFM3 Series of Models, Including 1.7B Text, Vision, Audio, and Omni Versions

    Liquid AI has released the LFM3 series of open-weight models, all branched from LFM3-1.7B-Base, covering text, vision, audio, Omni, and the d1 decision model. LFM3-1.7B-Base adopts a three-hybrid-layer architecture, is pretrained on 22T tokens, and in the mid-training stage over the final 3.5T tokens incorporates more agent trajectories and tool-calling data, with the context window extended to 256K tokens. The company says LFM3-1.7B is about 25% faster than LFM2-1.2B at an 8K context, and scores 38.42 versus 3.02 on WebArena-Verified; LFM3-VL-2B's average score across 62 vision benchmarks rises from 57.6 to 71.4. All models are available for download on Hugging Face, along with a single-GPU fine-tuning notebook.

    Liquid AI has released the LFM3 series of open-weight models, all branched from LFM3-1.7B-Base, covering text, vision, audio, Omni, and the d1 decision model. LFM3-1.7B-Base adopts a three-hybrid-layer architecture, is pretrained on 22T tokens, and in the mid-training stage over the final 3.5T tokens incorporates more agent trajectories and tool-calling data, with the context window extended to 256K tokens. The company says LFM3-1.7B is about 25% faster than LFM2-1.2B at an 8K context, and score

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    #lab#Model releases#Open-source ecosystem#English text is being prepared.
  5. Google DeepMindSelected

    Google DeepMind releases world model Genie 4, supporting native audio and real-time interaction

    Google DeepMind has released the world model Genie 4, which can generate interactive worlds in real time and, for the first time, natively generate ambient sound and character dialogue. The model builds on capabilities from the Gemini series; Gemini 3.8 Flash breaks down goals in a loop and checks frames to maintain causal coherence across multi-step events, and Gemini 4 Argon has also been used for joint simulation tasks with Gemini Robotics. The company says it remains an early experimental model: over long runs, object permanence and complex physical interactions still drift, all generated content carries a SynthID watermark, and it is currently available in preview to trusted testers first.

    Google DeepMind has released the world model Genie 4, which can generate interactive worlds in real time and, for the first time, natively generate ambient sound and character dialogue. The model builds on capabilities from the Gemini series; Gemini 3.8 Flash breaks down goals in a loop and checks frames to maintain causal coherence across multi-step events, and Gemini 4 Argon has also been used for joint simulation tasks with Gemini Robotics. The company says it remains an early experimental mo

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    #lab#Model releases#Multimodal#Video
  6. Google BlogSelected

    Google DeepMind Releases Gemini 4 Carbon Frontier Model

    Google DeepMind has released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0 and leading on SEC-bench Pro (88.2%), ExploitGym (54.8%), and CWE-bench (71.0%). The model targets long-horizon engineering tasks; an internal team once had it run continuously for several days to investigate and fix hidden defects in a large codebase, and it rose 89 elo to 4th place (1768) on WebDev Arena. Starting this week, Carbon will first be opened to some cybersecurity defenders, then gradually expanded through the Fairwind Program, and only afterward made available to developers, enterprises, and consumers; after the introductory period, pricing will be $4 per 1M input tokens and $20 per 1M output tokens.

    Faceted iridescent crystal surrounded by floating white number 4s.

    Google DeepMind has released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0 and leading on SEC-bench Pro (88.2%), ExploitGym (54.8%), and CWE-bench (71.0%). The model targets long-horizon engineering tasks; an internal team once had it run continuously for several days to investigate and fix hidden defects in a large codebase, and it rose 89 elo to 4th place (1768) on WebDev Arena. Starting this week, Carbon will f

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    #lab#Model releases#Safety / alignment#Agents
  7. Google DeepMind

    Google DeepMind Releases Gemini 4 Carbon, Focused on Cybersecurity and Long-Horizon Task Capabilities

    Google DeepMind has released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and achieving 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model is aimed at long-horizon engineering tasks; an internal team once had it run continuously for several days to investigate and fix hidden defects in a large codebase, and it rose to 4th place on WebDev Arena with 1,768 points. Starting this week, Carbon is first being made available to select cybersecurity defenders, then gradually expanding through the Fairwind Program, and only afterward to developers, enterprises, and consumers; after the introductory period, pricing is $4 per 1 million input tokens and $20 per 1 million output tokens.

    Faceted iridescent crystal surrounded by floating white number 4s.

    Google DeepMind has released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and achieving 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model is aimed at long-horizon engineering tasks; an internal team once had it run continuously for several days to investigate and fix hidden defects in a large codebase, and it rose to 4th place on WebDev Arena with 1,768 points. Starting this week, Ca

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    #lab#Model releases#Agents#English text is being prepared.

Tuesday

  1. Microsoft AI BlogSelected

    Microsoft Releases Image Editing Model MAI Image 2.7, Ranked 3rd on Arena Edit

    Microsoft AI has released the image editing model MAI Image 2.7, launched in preview form, ranking 3rd on Arena Edit and 2nd on the Artificial Analysis image editing leaderboard, making Microsoft AI the 2nd-ranked lab. The company states that the model outperforms 2.6 on all 10 use cases and 7 categories of editing actions evaluated by Artificial Analysis, leading the next-best model by 24 Elo in scenes and styles. It is currently available for trial on Arena, Artificial Analysis, and MAI Playground, with text-to-image functionality coming soon.

    Blurry, light-colored flowers against a blue sky.

    Microsoft AI has released the image editing model MAI Image 2.7, launched in preview form, ranking 3rd on Arena Edit and 2nd on the Artificial Analysis image editing leaderboard, making Microsoft AI the 2nd-ranked lab. The company states that the model outperforms 2.6 on all 10 use cases and 7 categories of editing actions evaluated by Artificial Analysis, leading the next-best model by 24 Elo in scenes and styles. It is currently available for trial on Arena, Artificial Analysis, and MAI Playgr

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    #company#Model releases#Image generation#Microsoft
  2. gihyo.jpSelected

    OpenAI releases GPT-6.1 Terra, with API pricing at half that of GPT-5.6 Terra

    On October 26, 2026, OpenAI released and made available GPT-6.1 Terra, strengthening visual understanding, computer operation, and writing capabilities. The standard API price is half that of GPT-5.6 Terra, namely $1 per million tokens for input, $0.05 for cached input, and $5 for output. The model has a context window of 1.05 million tokens, a maximum input of 922,000 tokens, and a maximum output of 128,000 tokens. Reasoning effort can be selected from none to max, with medium as the default. On Agents' Last Exam, the medium setting scores 15 points higher than GPT-5.6 Terra while costing about one-third as much; under the max setting, the average speed for completing tasks is more than 3 times that of GPT-6 Astra and GPT-6.1 Sol. The model is already available to Plus, Pro, Enterprise, and Edu users of ChatGPT Work and Codex, and the API model ID is gpt-6.1-terra.

    On October 26, 2026, OpenAI released and made available GPT-6.1 Terra, strengthening visual understanding, computer operation, and writing capabilities. The standard API price is half that of GPT-5.6 Terra, namely $1 per million tokens for input, $0.05 for cached input, and $5 for output. The model has a context window of 1.05 million tokens, a maximum input of 922,000 tokens, and a maximum output of 128,000 tokens. Reasoning effort can be selected from none to max, with medium as the default. O

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    #hot-signal#Model releases#Agents#Reasoning