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374 stories · Last updated November 14, 2026

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AI Models

Google’s Gemini 4 Hydrogen beats Argon on an outside test

Google’s new fast model costs $1.50 per million input tokens and $7.50 per million output tokens. Artificial Analysis, an independent testing firm, scores it 51 at its default setting, against 50 for the bigger Gemini 4 Argon. It is rolling out in the Gemini app, Search and the API.

Google released Gemini 4 Hydrogen on November 12 as the fast, everyday model of its Gemini 4 family. It follows Gemini 3.8 Flash. Google also added Orchestrator to Antigravity, its coding app, which switches between models within one session.

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AI Models

Google opens Gemini 4 Carbon to paying users

Paying developers, businesses and Google AI Ultra subscribers can now use Google’s strongest model. It costs $2 per million input tokens and $10 per million output tokens until November 30, then twice that. An outside test group scores it 60, behind Claude Fable 5.2 at 65.

Google made Gemini 4 Carbon available on November 10, two weeks after giving it first to a group of cyber defenders. It also started a preview of /swarm in Antigravity, its coding app, which turns one prompt into a team of AI agents.

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AI Models

Anthropic cuts Fable’s price 20% with its new 5.2 models

Claude Fable 5.2 is open to all users at $8 per million input tokens and $40 per million output tokens. Mythos 5.2, the same model with fewer safeguards, is only for vetted organisations. An outside test group scores Fable 5.2 at 65.

Anthropic released Claude Fable 5.2 and Claude Mythos 5.2 on November 9. It says they write answers up to 30% faster than the 5.1 versions. Artificial Analysis, an outside test group, puts Fable 5.2 among the leading models, but calls it particularly expensive.

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AI Models

Meta’s Muse Ember matches Haiku 5.5 at a third of the cost

Artificial Analysis scores Meta’s smallest model 36 on its index, the same as Claude Haiku 5.5 (max). A test task cost $0.14, against $0.41 for Haiku 5.5. The prices per token are the same; Ember saves by writing fewer tokens.

Meta released Muse Ember on November 9 for the work AI agents repeat all day, such as tool calls, coding subtasks and reading long documents. It costs $0.10 per million input tokens and $0.50 per million output tokens on the Meta Model API.

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AI Models

Thinking Machines launches Inkling 2 Small, weights to come

The model scores 31 on Artificial Analysis’s index, level with Gemini 3.8 Flash (high). It would be the top open model from outside China, but its weights are not public yet. Thinking Machines plans them for next week, after safety tests.

Thinking Machines Lab, founded by former OpenAI technology chief Mira Murati, released Inkling 2 Small on November 5. For now it runs only on the company’s Tinker service. The company plans to publish the weights under an Apache 2.0 licence once outside safety testing ends.

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AI Models

Kimi K3.1 Pro’s weights are out, and Tencent launches Hy4

Moonshot’s 2.8-trillion-parameter model can now be downloaded, under a custom licence with limits for the biggest businesses. Tencent’s Hy4 adds vision and computer use, but its weights are only promised “in the coming days”.

Moonshot AI has published the full weights of Kimi K3.1 Pro on Hugging Face, keeping its promise to do so by November 4. Anyone can download them without asking. On November 4, Tencent launched Hy4 in its apps and through its API. Tencent says Hy4’s weights will follow soon, so for now only the August preview can be downloaded.

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AI Models

Mistral releases the weights of its Large 4 model

Anyone can now download the 1-trillion-parameter model, under Mistral’s own licence. Mistral says it ties China’s GLM-5.3 at coding, but Artificial Analysis scores it one point lower there and further behind overall.

French company Mistral AI published the weights of Mistral Large 4 on Hugging Face on October 29, three weeks after a public preview. The model, nicknamed “Le Chonk”, has about 1 trillion parameters, and about 50 billion of them work on each token. Its API costs $0.70 per million input tokens and $2.10 per million output tokens.

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AI Models

Nvidia’s open Nemotron model transcribes 40 languages

Nemotron 3.5 Transcribe turns recordings into text, translates and labels who is speaking. Anyone can download it for commercial use, and Nvidia also released labels for 463,062 hours of speech.

Nvidia released Nemotron 3.5 Transcribe on Hugging Face on October 28. It is an open-weight model that writes down speech in 40 languages, and Nvidia says it translates 31 of them to or from English. It can tell up to eight speakers apart. Nvidia also published Granary v2, a large set of labels for training speech models.

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AI Models

Google’s Gemini 4 Carbon tops a new independent test

Google calls Carbon its strongest model, with top cybersecurity skills. Only some cyber defenders get it this week. Artificial Analysis already ranks it first, one point ahead of Anthropic’s Claude Opus 5.5.

Google announced Gemini 4 Carbon on October 28, two weeks after Gemini 4 Argon reached paying users. It goes first to a small group of cyber defenders and then to more trusted partners, Google says. There is no public app or API yet. Artificial Analysis, an independent testing firm, scores it 59 on its new Intelligence Index, the highest of any model.

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AI Models

Google’s Genie 4 builds worlds with sound you can steer

Google DeepMind’s new world model makes interactive scenes with sound and speech, and users can change them by typing. For now only trusted testers can use it, and nobody outside Google has tested its claims.

Google DeepMind released Genie 4 as a research preview for trusted testers on October 27. The model creates a world that people can move through, drawn frame by frame as they go, and change with text prompts. Google says Google AI Ultra subscribers and some developers will get it soon, but has given no date or price.

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AI Models

OpenAI’s GPT-6.1 Terra costs less and scores higher

OpenAI’s new mid-size model costs $1 per million input tokens and $5 per million output tokens, down from $2 and $12. The independent tester Artificial Analysis finds it scores 6 points more than GPT-5.6 Terra at less than a third of the cost per task.

OpenAI released GPT-6.1 Terra on Monday, October 26, in its API and for paying users of ChatGPT Work and Codex. Artificial Analysis ranks it 25th of 221 models on its Intelligence Index, with a score of 48. OpenAI’s claims about speed and its biggest model are not checked yet.

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AI Models

OpenAI says its AI proved a famous computing idea wrong

OpenAI says an internal model showed that the Exponential Time Hypothesis, a widely used assumption about how hard some problems are, is false. It also claims new proofs in maths and physics. No outside expert has confirmed any of them yet.

OpenAI announced the three claimed results on Monday, October 26, and put the computer science proof and a Lean version on GitHub. Three experts, two of whom first proposed the hypothesis, will lead an open check. They say their role does not mean the claim is right.

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AI Models

Moonshot launches Kimi K3.1 Pro, open weights due Nov 4

The Chinese company says its new model nearly matches Claude Opus 5.5 on a coding test. The independent tester Artificial Analysis scores it 55 points, fourth of 215 models, but the weights are not out yet.

Moonshot AI released Kimi K3.1 Pro on October 23, together with a faster version called K3.1 Pro Highspeed. Both work in Kimi’s apps and through its API. Moonshot says it will publish the full model weights by November 4, 2026, so anyone could then download and run the model.

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AI Models

Google Cloud starts offering OpenAI’s GPT-6 models

GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna are in a private preview for some business customers now. OpenAI says wider access follows in the coming weeks.

Google Cloud customers can buy OpenAI’s models through Google’s marketplace and pay with their existing cloud budgets. The models are also coming to Google’s Antigravity coding tool.

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AI Models

doubleAI says its Maxwell model makes code run faster

The startup of Mobileye’s founder says Maxwell rewrites programs while they run, so they use chips better. Its speed-ups are its own figures, and it also announced a $200 million round backed by Nvidia.

doubleAI, an Israeli startup led by Mobileye founder Amnon Shashua, has launched Maxwell, which it calls a “code execution model”. Maxwell watches a program while it runs and rewrites its machine code to use CPUs and GPUs better. It is open to early-access customers only.

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AI Models

MiniMax launches M3.1 Flash at half the price of M3

The Chinese company says its new agent model is nearly three times faster and 70% cheaper to use. Artificial Analysis ranks it fourth of 173 models, but measured a lower speed and a 93% hallucination rate.

MiniMax, a Chinese AI company, released M3.1 Flash on October 19. It costs $0.15 per million input tokens and $0.60 per million output tokens, half the price of MiniMax-M3. The independent tester Artificial Analysis gives it 42 points on its index, fourth of 173 models.

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AI Models

GoTo releases a free AI model for Indonesian and Javanese

The 27-billion-parameter model also handles Sundanese, Balinese and Batak Toba. It is built on Google’s Gemma 3 with AI Singapore, and its weights are free under Google’s Gemma licence.

GoTo, the Indonesian group behind the Gojek and Tokopedia apps, released GoTo-AI-Gemma-3-27B-IT on October 19. The model works in Indonesian, English and four regional languages, and anyone can download it from Hugging Face. GoTo says it scored highest on every regional language in its own tests, but it has published no scores.

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AI Models

DeepSeek releases an open update of its V4.1 Flash model

DeepSeek says the new version scores higher on coding and agent tests, finishes tasks faster and writes shorter answers. Anyone can download it under the MIT licence, and no outside group has tested it yet.

DeepSeek released DeepSeek-V4.1-Flash-1017 on October 17, a “minor update” to the V4.1 Flash model it launched on September 10. The weights are on Hugging Face, and the API price stays the same. In DeepSeek’s own table, the model scores 77.0 on the DeepSWE coding test, up from 74.2.

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AI Models

Microsoft finishes pre-training its 2.8T MAI-Base-2 model

The model has 2.8 trillion parameters and is not released yet. Microsoft says it beats every open-weight model it tested and needs 4.2 to 12.3 times less computing power than DeepSeek’s best base model; no outside group has checked this.

Microsoft AI said on October 15 that it has finished pre-training MAI-Base-2, its largest model so far. It is a mixture-of-experts model with 2.8 trillion parameters, of which 80 billion work on each token. The model is now in a second stage of training, and Microsoft gives no release date.

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AI Models

Meta releases Muse Spark Open, an 816B open-weight model

Meta calls it the most capable open-weight model from a US company. An independent test gives it 39 points, and in Meta’s own table two Chinese open models still lead on coding.

Meta released the weights of Muse Spark Open on October 15. The model has 816 billion parameters, of which about 42 billion work on each token, and it can read up to 1 million tokens at once. Meta worked with Apple so the model can run on two or four linked Mac Studio computers.

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AI Models

Google opens Gemini 4 Argon to paying users and developers

Since October 13, AI Pro and Ultra subscribers can use it in the Gemini app and in Search, and developers through the paid API. Free users don’t get it yet, and the launch price doubles on December 1.

Google released Gemini 4 Argon, its newest flagship model, to many more people on October 13, two weeks after it went only to cyber defenders. Subscribers to Google AI Pro and Ultra can use it in the Gemini app and in AI Mode in Search. Developers can use it through the paid Gemini API. Free users and AI Plus subscribers don’t get it for now.

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AI Models

Meta’s Muse Wonder models close in on the AI frontier

Meta released Muse Wonder and the larger Muse Wonder Full on October 12. On Artificial Analysis’s index, Wonder Full scores 56, two points behind Claude Opus 5.5.

Meta released two new AI models, Muse Wonder and Muse Wonder Full, built for agents that work on long tasks. Developers can use Muse Wonder through Meta’s API for $4 per million input tokens and $20 per million output tokens. Muse Wonder Full is only for paying users of Muse Code, Meta’s coding agent.

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AI Models

Microsoft launches Decision-1, a fast model for AI choices

The model is built on Alibaba’s open Qwen3.5-9B and costs the same as Jev. Microsoft says it beat its rivals on 36 tests, and no outside group has checked that yet.

Microsoft released Microsoft-Decision-1 on October 9. It is a small model that scores a fixed list of options, such as yes or no, and gives a probability for each. It runs in Microsoft Foundry and on OpenRouter for $0.042 per million input tokens. Microsoft says it will soon rebuild it on its own models and on OpenAI’s.

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AI Models

Leaderboard Arena raises $200M and grades agents’ behaviour

Arena says the round values it at $3.1 billion, almost double its value in January. Its new Alignment Index counts how often AI agents act without permission or claim work is done when it is not.

Arena, which runs a popular public leaderboard of AI models, said on October 8 that it raised $200 million at a $3.1 billion valuation. Lightspeed and Khosla Ventures led the round. Arena also launched a preview of its Alignment Index, which scores 27 models on how they behave as agents in real sessions.

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AI Models

Anthropic’s Haiku 5.5 cuts small-model prices by 90%

The new small Claude model costs $0.10 per million input tokens for shorter requests, against $1 for Haiku 4.5. An outside test ranks it second of 182 models in its class.

Anthropic released Claude Haiku 5.5 on October 7. It costs $0.10 per million input tokens and $0.50 per million output tokens for requests up to 100,000 tokens. It is the first Haiku model with effort controls. Anthropic also halved a Sonnet 5.5 price and added monthly API credits for some plans.

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AI Models

Mistral previews Large 4, a 1-trillion-parameter model

The French lab says free weights will follow by the end of October. An outside test ranks the preview 64th of 225 models, above the middle of the field but far from the top.

Mistral AI opened a public preview of Mistral Large 4 on October 6. The model has 1 trillion parameters, of which 49 billion work on each token. Mistral says it will release the weights by the end of October, after testing the model with security experts and governments.

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AI Models

Reflection unveils Beam, an open model to rival China’s labs

The US start-up says its 501-billion-parameter model matches a top Chinese model with a quarter to a third of the computing. The weights come later this month, and no outside test exists yet.

Reflection AI announced Beam on October 5, its first open-weight model. The company says Beam scores like Z.ai’s GLM-5.2 on hard reasoning tests while using 3 to 4 times less computing to run. The weights, under the Apache 2.0 licence, are due later this month; for now there is only an early-access list.

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AI Models

Free Gemini users get mostly Flash-Lite from October 9

Without a plan, Gemini now picks the model: most prompts go to the smallest, Flash-Lite. The cheapest paid plan loses Pro, and AI Pro subscribers gain Deep Think.

Google has updated its Gemini help pages: from October 9, people using the Gemini app without a Google AI plan get Auto by default. Most prompts go to the Flash-Lite model, and harder ones may go to Flash or Pro. Subscribers to AI Plus keep Flash-Lite and Flash but lose Pro, on a date Google will send them by email.

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AI Models

Academic AI beats Stratego’s top player on a small budget

University researchers report in Nature that their Ataraxos AI beat four-time world champion Pim Niemeijer 15 games to one, with four draws. Training cost a few thousand dollars, they say.

Researchers from Carnegie Mellon, MIT, New York University and Stanford say their AI, Ataraxos, beat Stratego champion Pim Niemeijer in a 20-game online match. The work is published in Nature. Stratego hides the identity of each player’s pieces, which made it one of the last classic board games where top humans still beat machines.

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