Tencent Hunyuan releases the open-source free-form interactive video world model Hy-Nomas, which supports interaction using text prompts and camera trajectories, and features long-horizon generation with world memory. The model can be adapted to specialized domains such as robotics via lightweight LoRA, and has been optimized for consumer-grade GPU inference. The official release also provides website, GitHub, Hugging Face, and demo entry points.
Moonshot AI released the reasoning model Kimi K3.1 Pro, which scored 55 on the Artificial Analysis Intelligence Index, ranking fourth, an 11-point improvement over Kimi K3's 44 points, behind only Claude Opus 5.5 (58), Claude Sonnet 5.5 (56), and Muse Wonder Full (56). Its agentic capabilities improved markedly: it ranks third on GDPval-AA with 1846 Elo, scores 67% on Terminal-Bench 4.0 (Kimi K3 scored 13%), and rose from 58% to 73% on AutomationBench-AA. The model has a 1M-token context window, 2.8T total parameters with 104B activated parameters, supports text and image inputs, is priced at $2/10/0.20 per 1M input/output/cache-hit tokens, and its weights have not yet been released.
Moonshot AI released the reasoning model Kimi K3.1 Pro, which scored 55 on the Artificial Analysis Intelligence Index, ranking fourth, an 11-point improvement over Kimi K3's 44 points, behind only Claude Opus 5.5 (58), Claude Sonnet 5.5 (56), and Muse Wonder Full (56). Its agentic capabilities improved markedly: it ranks third on GDPval-AA with 1846 Elo, scores 67% on Terminal-Bench 4.0 (Kimi K3 scored 13%), and rose from 58% to 73% on AutomationBench-AA. The model has a 1M-token context window,
Moonshot AI released the reasoning model Kimi K3.1 Pro, which scores 55 on the Artificial Analysis Intelligence Index, ranking 4th, an 11-point improvement over Kimi K3's 44 points, trailing only Claude Opus 5.5 (58), Claude Sonnet 5.5 (56), and Muse Wonder Full (56). Its agent capabilities improved notably: it scores 1,846 Elo on GDPval-AA, ranking 3rd; 67% on Terminal-Bench 4.0 (Kimi K3 was 13%); and AutomationBench-AA rose from 58% to 73%. The model has a 1M-token context window, 2.8T total parameters and 104B activated parameters, supports text and image input, and is priced at $2/10/0.20 per 1M input/output/cache-hit tokens, all three 33% lower than Kimi K3; the weights have not yet been released, and once released it will become the highest-scoring open-weight model, narrowing the gap between leading open-source and closed-source models from 12 points to 3 points.
Moonshot AI released the reasoning model Kimi K3.1 Pro, which scores 55 on the Artificial Analysis Intelligence Index, ranking 4th, an 11-point improvement over Kimi K3's 44 points, trailing only Claude Opus 5.5 (58), Claude Sonnet 5.5 (56), and Muse Wonder Full (56). Its agent capabilities improved notably: it scores 1,846 Elo on GDPval-AA, ranking 3rd; 67% on Terminal-Bench 4.0 (Kimi K3 was 13%); and AutomationBench-AA rose from 58% to 73%. The model has a 1M-token context window, 2.8T total p
MiniMax announced on October 23 the open-sourcing of the M3.1 Flash model, which processed over 100 trillion tokens within 72 hours of launch. Compared with the previous generation M3, M3.1 Flash has comprehensively improved capabilities, with usage cost reduced by 70% and online inference speed increased by nearly 3 times. MiniMax stated it will work with chip manufacturers such as Huawei Ascend, NVIDIA, and AMD, as well as inference frameworks and communities such as vLLM, SGLang, and Hugging Face, to advance day-one open-source integration.
MiniMax announced on October 23 the open-sourcing of the M3.1 Flash model, which processed over 100 trillion tokens within 72 hours of launch. Compared with the previous generation M3, M3.1 Flash has comprehensively improved capabilities, with usage cost reduced by 70% and online inference speed increased by nearly 3 times. MiniMax stated it will work with chip manufacturers such as Huawei Ascend, NVIDIA, and AMD, as well as inference frameworks and communities such as vLLM, SGLang, and Hugging
MiniMax M3.1 Flash weights are now public, with 428B total parameters and 23B activated per token. The company claims substantial improvements in agentic tasks, coding, and cybersecurity: BankerToolBench 76.2, DeepSWE v1.1 73.7%, OSWorld V2 61.7, Agents' Last Exam 29.6, CyberGym 82.2. The model uses MiniMax Sparse Attention and DSpark speculative decoding to improve inference efficiency; the weights are now available on Hugging Face and ModelScope, with API and MCode desktop entry points also provided.
MiniMax M3.1 Flash weights are now public, with 428B total parameters and 23B activated per token. The company claims substantial improvements in agentic tasks, coding, and cybersecurity: BankerToolBench 76.2, DeepSWE v1.1 73.7%, OSWorld V2 61.7, Agents' Last Exam 29.6, CyberGym 82.2. The model uses MiniMax Sparse Attention and DSpark speculative decoding to improve inference efficiency; the weights are now available on Hugging Face and ModelScope, with API and MCode desktop entry points also pr
Ant Ling announced the official open-sourcing of Ling-3.0-flash-Sante, a medical-enhanced MoE model with 124B total parameters that activates only 5.1B parameters per token; the company claims it leads models of the same scale in performance on professional medical tasks and complex medical reasoning. Beyond medical question answering, the model has also been strengthened for deep research, multi-agent collaboration, and tool calling, and its model weights are now available for download.
Recursive's first model Flint has launched on OpenRouter. It is an open-weight 40B MoE model (about 2.5B active parameters), built by the company's automated research system Eureka Machine, aimed at coding agents, and supports 262K context, reasoning, and tool calling. Recursive reports that it scores 54.9% on Terminal-Bench 2.1, 89.7% on SWE-bench Pro v2, and 74.2% on SWE-bench Verified, and is free to use during its launch period.
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.
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 autho
Gradium open-sources the Phonon on-device speech synthesis model suite, with all models under 50m parameters, focused on multilingual naturalness and accuracy, and claims to offer the broadest inference support to date. Phonon-31m is released under the Apache 2.0 license. Matt Turck reposted this news.
OpenAI has released GPT-6 Astra, a coding model for legacy programming languages such as COBOL, Fortran, and Visual Basic. OpenAI built two evaluations for this purpose, MultiLangBench and COBOL migration. GPT-6 Astra scored 87.4% on the 20 languages in MultiLangBench, compared with 26.8% for GPT-5.6 Sol; it scored 86.8% on COBOL migration, or 97.9% at high reasoning effort, while GPT-5.6 Sol scored only 5.4%. The model is now available to developers through the OpenAI API for coding tasks in COBOL, Fortran, OCam, and Visual Basic.
OpenAI has released GPT-6 Astra, a coding model for legacy programming languages such as COBOL, Fortran, and Visual Basic. OpenAI built two evaluations for this purpose, MultiLangBench and COBOL migration. GPT-6 Astra scored 87.4% on the 20 languages in MultiLangBench, compared with 26.8% for GPT-5.6 Sol; it scored 86.8% on COBOL migration, or 97.9% at high reasoning effort, while GPT-5.6 Sol scored only 5.4%. The model is now available to developers through the OpenAI API for coding tasks in CO
fal and BFL have partnered to release the post-trained video model FLUX 3 Max, with the team optimizing inference to improve output quality. The model scores 1,139 on the Artificial Analysis image-to-video index and generates up to 22 times faster than Seedance 2.5; fal says it can generate a 10-second 720/768p video in about 12 seconds, with a 75% price cut over the next three weeks.
Dream Labs exits stealth mode and releases the robot foundation model Dream-1, which can control dual-arm robots it has never seen before, perform tasks it has never been trained on, and enter locations it has never been to, starting at $3 per hour. The Dream API opens to everyone the same day, with its inference powered by fal Serverless.
MiniMax has released M3.1 Flash, which reaches frontier-level performance on tasks such as Cowork (Automation-Bench 62%, ALE 30%), coding (DeepSWE 74%), and visual reasoning (BabyVision 91%), at one-third the cost of M3 and 3x the speed. The unified API price is $0.15/$0.60 per 1M input/output tokens, with cache reads at $0.015 per 1M tokens. The company says Space Bunny, which previously topped global leaderboards and processed 200T+ tokens, is an early version of M3.1 Flash, and the model weights will be released on October 23.
MiniMax has released M3.1 Flash, which reaches frontier-level performance on tasks such as Cowork (Automation-Bench 62%, ALE 30%), coding (DeepSWE 74%), and visual reasoning (BabyVision 91%), at one-third the cost of M3 and 3x the speed. The unified API price is $0.15/$0.60 per 1M input/output tokens, with cache reads at $0.015 per 1M tokens. The company says Space Bunny, which previously topped global leaderboards and processed 200T+ tokens, is an early version of M3.1 Flash, and the model weig
