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AIGeneralist 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.

AIOdyssey 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.

AIPerplexity'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.

AICarbon-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.

AIThomas 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.

AIFish 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.

AIGeneralist (@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.

AIPerplexity'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.

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.

AIStepFun 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.

AIAnt 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.

AICognition'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.

AIGoogle 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.