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Recursive releases laptop-class coding model Flint, says it was built mainly with AI involvement

AI startup Recursive has released its first model, Flint, a coding model that runs offline on a laptop and is freely downloadable on Hugging Face under the Apache 2.0 license; the company says its development process was mainly carried out with the involvement of its in-house Eureka Machine. Flint is an MoE model that activates only 2.5B of its 40B parameters at a time, generates at about 131 tokens/sec on a MacBook Pro with an M4 Pro, and outperforms other models under 50B parameters on SWE-Bench Verified. Recursive says Flint requires more guidance than large paid coding assistants and recommends breaking large tasks into small steps.

MiniMax Releases M3.1 Flash Model, ALE Score of 29.6% Ranks First Among Domestic Models

MiniMax officially released M3.1 Flash, formerly known as Space Bunny (Yutu), which previously topped the charts anonymously on OpenRouter. The model scores 29.6% on Agents' Last Exam, ranking first among domestic models, and scores 43 on the AA leaderboard; it achieves 73.7% on DeepSWE v1.1, 82.2 points on CyberGym, 76.2 points on BankerToolBench, tying for first with Claude Opus 5, and 61.7 points on OSWorld V2. The model adopts a sparse attention architecture, with output speeds of up to 200+ TPS and a median of 170+ TPS, input at 1 yuan per million tokens, output at 4 yuan, and cache reads at 0.1 yuan, with comprehensive usage costs reduced by 70% compared to the previous generation M3.

MiniMax Releases M3.1 Flash, Scoring 29.6% on Agents' Last Exam to Rank First Among Chinese Models

MiniMax has officially released M3.1 Flash, the model previously known as Space Bunny (Yutu) that topped the charts anonymously on OpenRouter. It scores 29.6% on Agents' Last Exam, ranking first among Chinese models. The model achieves 73.7% on DeepSWE v1.1, 82.2 points on CyberGym, and 61.7 points on OSWorld V2, with output speeds of up to 200+ TPS and a P50 maintained at 170+ TPS. Pricing is 1 yuan per million input tokens, 4 yuan for output, and 0.1 yuan for cache reads.

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MiniMax Releases M3.1 Flash, Tested Frontend Coding Capabilities

MiniMax claimed the anonymous model Space Bunny on October 19 and officially released M3.1 Flash, which uses a sparse attention architecture with 428B total parameters and about 23B activated, nearly 3x faster inference, 70% lower usage cost, and pricing of 1 yuan per million input tokens, 4 yuan for output, and 0.1 yuan for cache reads. Model weights will be open-sourced on October 23, and the official announcement previews a Pro version with a higher intelligence ceiling coming soon. The author replaced the community-viral cases with four new questions of the same type for retesting, and believes its frontend Coding capabilities improved noticeably while retaining the self-verification behavior of proactively opening a browser to trial and error.

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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%.

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.

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Meta releases frontier model series Muse Wonder, focused on personal and professional agent tasks

Meta releases its first frontier model series Muse Wonder, including two models, Muse Wonder and Muse Wonder Full, focused on personal and professional agent tasks and introducing proactive memory and proactive focus capabilities. On DeepSWE 1.1 and SWE-Marathon tests, Muse Wonder Full scores higher than Claude Fable 5.1, GPT-6 Astra and Claude Opus 5.5; at the highest reasoning effort on the Artificial Analysis leaderboard, the two models' Intelligence Index scores are 52 and 56 respectively. Muse Wonder is priced at 4 USD per million input tokens and 20 USD per million output tokens; Muse Wonder Full is now available on the API platform and open to Muse Code subscribers.

Meta releases Muse Wonder and Muse Wonder Full, surpassing Claude on long-horizon coding tests…

Meta Superintelligence Labs launched its new-generation flagship models Muse Wonder and Muse Wonder Full on October 13. The Full version scored 56 on the Artificial Analysis Composite Intelligence Index, 2 points behind Claude Opus 5.5's 58. On the DeepSWE 1.1 long-horizon software engineering test, Wonder Full scored 79.0, surpassing Opus 5.5's 74.2 and GPT-6 Astra's 74.1, but it still trails Opus on Terminal-Bench 4.0 and ProgramBench. Artificial Analysis estimates its average task cost at $4.52, up 183% from the previous generation Muse Spark 1.3; a developer comparison on the same prompt shows its 3D game generation is noticeably worse than Opus, and Meta's model card has acknowledged 3D tasks as a known limitation.

Meta releases the Muse Wonder series of models, focused on personal agent memory and long-horizon tasks

Meta released two models, Muse Wonder and Muse Wonder Full, internally codenamed Watermelon, targeting personal and professional agent tasks, with a focus on improving cross-conversation memory and long-duration task execution. Artificial Analysis evaluations show that Wonder Full placed in the top three on six of ten tests, and at the highest reasoning intensity, Muse Code paired with Wonder Full matches Claude Code paired with Sonnet 5.5 in coding performance. API pricing is $4 per million input tokens and $20 per million output tokens; Wonder Full is available only to Muse Code subscribers, and Meta AI head Alexandr Wang acknowledged that its coding capability still lags behind Opus 5.5.

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Google Releases Gemini 4 Argon, Topping Multiple Leaderboards and Focusing on Cybersecurity Defense

Google has released its new-generation flagship model Gemini 4 Argon, which scores 77.9% on DeepSWE v1.1, surpassing Claude Opus 5.5's 74.2% and GPT-6 Astra's 74.1%, and tops the Vals Index with 68.90%. The model supports output of up to one million tokens, and during the promotional period costs $2 per million input tokens and $10 per million output tokens, with a per-question cost of about 40% of Astra's. It is currently available only to vetted cybersecurity defense teams, with the first batch entering Google's Fairwind program.

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English translation is being prepared.