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elvis@omarsar0AI score42AIOdyssey released Odyssey-3 Pro, which sets a new top score on Physics-IQ Verified, a benchmark where models continue videos of real physics experiments. In robotics, a robot arm with tens of hours of demonstrations recovered from a missed grasp, a behavior absent from those demos.
Generalist@GeneralistAIAI score28AIGeneralist has announced GEN-1.5, its latest foundation model for the physical world. The post provides only a link to the company's blog for further details, so no specifications, benchmarks, or availability information can be confirmed from this source.
Generalist@GeneralistAIAI score13AIGeneralist's GEN-1.5 is shown repeatedly packing bottles into boxes, one after another. The post links to a blog post with more details about the model.
Santiago@svpinoAI score46AIOdyssey 3 Pro, a world model, is now live as a research preview and ranks first on the Physics-IQ Verified video-to-video benchmark. The post says it can learn from visual observations and map that knowledge to physical controls for robots, cars, video games, and drones. Odyssey-3, the model launched alongside it, is described as free to try.
Odyssey@odysseymlAI score31AIOdyssey has released Odyssey-3, which it describes as a major leap toward world models that power physical AI, generate training environments, and enable new human experiences. The post invites readers to try Odyssey-3 at the company's website but gives no specific benchmarks, parameter counts, or pricing.
Odyssey@odysseymlAI score34AIOdyssey says its Odyssey-3 model's learned world knowledge can be adapted by physical AI developers to control robots, power humanoids, drive cars, and fly drones. The post describes this as a capability for autonomous machines generally, without providing benchmarks, specifications, or availability details.
Odyssey@odysseymlAI score38AIOdyssey announced Odyssey-3, a foundation world model it says enables applications in physical AI, human experiences, and training intelligences. The company highlights agents learning from experience inside Odyssey-3 while working toward objectives.
Odyssey@odysseymlAI score22AIOdyssey-3 Pro achieved a score of 66.1 on Physics-IQ Verified's video-to-video benchmark, the highest reported score so far. Physics-IQ evaluates physical behavior across fluid dynamics, optics, solid mechanics, magnetism, and thermodynamics.
Odyssey@odysseymlAI score40AIOdyssey has launched Odyssey-3, which it describes as its most powerful foundation world model yet. The company says the model sets a new state of the art on Physics-IQ and can power robots, train AIs, and generate interactive experiences, and it is available to try for free today.
Odyssey@odysseymlAI score42AIOdyssey-3 is a new world simulator that generates interactive environments from a prompt in real time. It learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations.
Aravind Srinivas@AravSrinivasAI score22AIPerplexity's Decider V1.1 ranked first on DecisionBench while also having the lowest cost, according to a post highlighting the result. The benchmark results cited include 949 shared text cases, 93.9% accuracy, a 534 ms median latency, and $0.016 per 1k decisions.
AIJetBrains has released Mellum2.1, a 12B mixture-of-experts thinking model with 2.5B active parameters, under Apache 2.0 on Hugging Face. Post-training reinforcement learning in real software repositories raised SWE-bench Verified from 2.0 to 47.0, according to JetBrains' self-reported results. Qwen3.5-9B still leads on SWE-bench Pro, GPQA Diamond and AIME, and GGUF builds start at 7.0 GB for local use.
Arena.ai@arenaAI score55AIArena announced a $200M Series B at a $3.1B valuation and released its Alignment Index, a benchmark measuring agent safety and alignment. The index is built from 90K+ real-world agent sessions across 27 models and tracks Unauthorized Action, False Attribution, and Deceptive Completion. OpenAI's GPT-6.1-Sol leads with a score of 87.9, ahead of Claude-Opus-5.5 at 83.2 and Grok-4.7 at 82.7.
Sophia Yang@sophiamyangPickAI score60
Leandro von Werra@lvwerraPickAI score70AICarbon-A is an open model that predicts gene locations directly from DNA, and it has been used to annotate genomes from over 22,000 species. The release includes a database of 566 million gene candidates, about 16 times the gene annotations in the RefSeq dataset. Wet-lab RNA experiments supported 239 candidates missing from RefSeq across cats, Syrian hamsters, chickens, and Arabidopsis.
Why it matters: The source ties an open gene-annotation model to specific wet-lab checks and gene counts, helping readers judge how far its predictions extend beyond well-studied genomes.
Thomas Wolf@Thom_WolfSame storyAI score67AIThomas Wolf says Carbon-A, an open model that finds genes directly in DNA, has been released with a database of 566.34 million candidate genes across 22,617 species. The team reports wet-lab validation of several new genes in cats, chickens and arabidopsis, and RNA evidence for 239 genes missing from reference annotations of common species.
This story has a top pick“Carbon-A open model and database predict 566 million gene candidates across 22,617 species”
elvis@omarsar0AI score32AIFish Audio's Drama 3 voice model lets users direct tone, emotion, and pacing in plain language, and can shift emotion mid-sentence. The poster, who found it remarkably effective in testing, says the control over delivery is unlike anything previously seen. A preview is available through the API as drama-3-preview.
AIAnthropic released Claude Haiku 5.5, raising its OSWorld 2.1 score from 15.7% to 72.4% and supporting a 1 million token context window. The article notes Haiku 5.5 still scores 39.2% on Terminal-Bench 4.0 against Sonnet 5.5's 70.6%, and that prompts above 100,000 tokens are priced higher, so migration costs need to be measured on real workloads.
Generalist@GeneralistAIAI score14AIGeneralist (@GeneralistAI) has introduced GEN-1.5, its latest foundation model for the physical world. The post links to a playlist of other tasks its models can perform and to a blog post with further details on GEN-1.5.
Aravind Srinivas@AravSrinivasAI score40AIPerplexity's pplx-decider v1.1 scored 643 of 669 on clinical decisions versus 628 for Jev, according to a quoted post. The quoted post says it costs 42% less per decision at about the same speed and that its weights can be downloaded and run inside hospitals.
OpenRouter@OpenRouterAI score14AIOpenRouter says GPT-6 Luna is currently the fastest Decisions model, at 180ms on global requests. The post also places Jev and Perplexity Decider as following models, but gives no further figures.
OpenRouter@OpenRouterAI score29AIStepFun's Step 5 Preview outperforms Kimi K3 and GLM-5.3 on six of eight benchmarks in its own evaluation. Reported scores include 67.7 on DeepSWE, 80.5 on ProgramBench, 49.0 on StepCodeBench, and 66.4 on FrontierFinance.
OpenRouter@OpenRouterAI score44AIStepFun's Step 5 Preview is now live on OpenRouter as the company's new flagship for agentic work. It uses a sparse MoE design with 27B active and 600B total parameters, a 1M context window, and accepts text, image, and video input. The post highlights strength in coding and professional knowledge work, especially finance.
AITypeSafe AI released Jev, a model that answers yes/no, multiple-choice, or rating questions by outputting the estimated probability of each option. The author notes this design lets the model be served faster and more cheaply than LLMs and fits ordinary if-statement logic, and says he used it to flag spam comments on his blog in place of Gemini 3 Flash.
StepFun@StepFun_aiAI score18AIStepFun is promoting Step 5 Preview, pointing readers to a model overview, benchmarks, and demos on its website. The post also links to technical specifications and API documentation for developers.
AIStepFun has released Step 5 Preview, its flagship model for agentic work, built on a sparse Mixture-of-Experts architecture with 27B active and 600B total parameters. The source says it performs strongly in software engineering and professional tasks, but the feed supplied only an excerpt, so benchmark details are not available here.
AIJetBrains released Mellum2.1, a 12B mixture-of-experts model with 2.5B active parameters under the Apache 2.0 license, built for coding agents. Post-training shifted to reinforcement learning across thousands of environments and millions of sandboxed runs, and the model is available on Hugging Face. The source reports gains over Mellum2 on LiveCodeBench, AIME, GPQA Diamond, BFCL v4, IFEval, and SWE-bench Verified, and says it serves almost twice the tokens of Qwen3.5-9B under heavy load.
Why it matters: The post shows how reinforcement learning in real sandboxed environments changed a compact open model's repository work, with benchmark gains against Mellum2 and two peers.
AIAnthropic released Claude Haiku 5.5, its fastest and most affordable small model, at prices up to 90 percent lower for most prompts under 100,000 tokens. Artificial Analysis ranks it first among small-class models on its Intelligence Index with a score of 43, but it consumes about three times the output tokens per task that GPT-6 Luna needs at maximum effort.
Ant Ling@AntLingAGIAI score22AIAnt Ling announced a day-zero collaboration with AI/ML API, making Ling-3.1-flash available there for agentic and cowork scenarios. AI/ML API describes it as a 560B-parameter MoE model with about 25B active per token and up to 1M context, built for agents, coding, and long documents. The model is free to try on AI/ML API until October 13.
AIAnthropic released Claude Haiku 5.5, priced the same as OpenAI's GPT-6 Luna, with a 1M-token context window. Artificial Analysis scored it 43 on its Intelligence Index, slightly ahead of GPT-6 Luna at 38, but it uses about 3x more output tokens at max effort.
AIPerplexity has released pplx-embed-v2-late, a pair of ColBERT-style multimodal embedding models in 0.6B and 9B sizes that retrieve text, images and rendered PDF pages in a shared embedding space. Both are available on Hugging Face under the MIT license, while a hosted API endpoint is planned but not yet live.
AIArtificial Analysis is adding trusted-access models to its Cyber Index, starting with GPT-6 Sol (Daybreak Blue, max), which is available only through OpenAI's Daybreak program. The model hits no safety blocks across the Index and scores 32 points higher overall than the publicly available GPT-6 Sol (max), with its largest gains on CyberGym-E2E.
Why it matters: The source shows how safety refusals shape cyber benchmark scores, with the trusted-access model's gains concentrated on CyberGym-E2E, useful for comparing guarded and unguarded models.
AIFrench AI company Mistral has released Mistral Large 4, its new flagship model with 1 trillion total parameters. The company plans to make all of the model's weights open at the end of the month.
AIAnthropic released Claude Haiku 5.5, which it calls the fastest, cheapest, and most capable Haiku model so far. On average it costs about 75% less to run than Haiku 4.5, with input at $0.10 and output at $0.50 per million tokens for requests up to 100,000 tokens. Anthropic also cut Sonnet 5.5's cache read price from $0.20 to $0.10 per million tokens, which it says lowers run costs by about 20% on many agent tasks.
Cognition@cognitionAI score26AICognition's X post links to a blog post at devin.ai about Claude Haiku 5.5, but the text provides no further details. The post itself offers no benchmark scores, prices, or capabilities to report.
AIAnthropic has released Claude Haiku 5.5, priced at $0.10 input and $0.50 output per million tokens up to 100,000 tokens, matching GPT-6 Luna. Beyond 100,000 tokens the price rises to $0.50 and $2.50, and the author found the new tokenizer uses about 1.25x as many tokens as Haiku 4.5 on the same long prompt. The model cannot disable reasoning and defaults to medium effort.
AIAnthropic has released Claude Haiku 5.5, its cheapest and fastest small model, priced at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens. It keeps a 1M token context window, up to 128K output tokens, and is generally available on the Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry and Claude Platform on AWS. Anthropic reports 72.4% on OSWorld 2.1 (offline subset) versus 15.7% for Haiku 4.5, and the article notes that non-default temperature, top_p or top_k values return a 400 error.
Google Flow@FlowbyGoogleAI score27AIGoogle says users are already testing its newest image generation model, Nano Banana 2.1, and shares examples of the early results. The post provides no benchmark scores, pricing, or capability details.
Google Flow@FlowbyGoogleAI score23AIGoogle Flow says its model excels at maintaining consistency after multiple edits. A test by @pleometric, reconstructing an image 100 times with the prompt "reconstruct this exactly as it is," found 2.1 best preserved the original subject compared with other Nano Banana models.
Alex Albert@alexalbert__AI score39AIAnthropic's Claude Haiku 5.5 is much faster and 75% cheaper than Haiku 4.5, which launched October 15, 2025, less than a year earlier. Anthropic describes it as a significant step up over Haiku 4.5 across coding, computer use, and knowledge work.
