Updated
Updated
Items with an AI score under 20 are hidden. Show low-relevance items
Tibor Blaho@btibor91AI score52AIIdeogram has launched Ideogram 4.5, an image editing model that is now live in Ideogram, the API, and launch partners. Open weights are coming soon. The launch post says the model avoids artifact buildup and pixel shifts across repeated edits, making multi-turn editing possible.
Ideogram@ideogram_aiAI score46AIIdeogram 4.5 comes in four quality modes, ranging from 0.8¢ to 22¢ per image, all at native 2K resolution. Available now on our launch partners: @superscale_ai @Picsart @cfabricacom @luminal_ai @arena @runware @florafaunaai @krea_ai @trymoda @LeonardoAi @runwayml @pika_labs @fal @ComfyUI @magnific @GammaApp @LumaLabsAI @DesignArena
Ideogram@ideogram_aiAI score22AIIdeogram posted a side-by-side test of identical edits on Ideogram 4.5, GPT Image 2.5 Sunburst, Nano Banana Pro, and Nano Banana 2. The post claims GPT Image and Nano Banana outputs become unusable within a few edits, while Ideogram 4.5 remains clean across repeated edits.
Ideogram@ideogram_aiAI score38AIIdeogram released Ideogram 4.5, which it calls the most precise edit model, claiming it avoids the artifacts, pixel shifts, and color changes that leading models add with each edit. The company says this eliminates artifact buildup and makes multi-turn editing possible. It is live in Ideogram, via the API, and with launch partners, with open weights promised soon.
Aidan Gomez@aidangomezAI score38AICohere has introduced Embed 5, a new family of state-of-the-art embedding models, with Embed 5 Pro for frontier capabilities and Embed 5 Fast for low-latency performance. The post says the models are extremely scalable, offer SOTA accuracy, and can be deployed privately and accessed through Model Vault.
ModelScope@ModelScope2022AI score46AIIndexTeam has released Index-Translate, a multilingual family covering text, speech, dubbing, and long-document translation across 150 languages. Its 9B model scores 0.8789 on FLORES, 0.8209 on instTrans, and 0.7387 on MEME, and the 2B and 9B models are released under Apache 2.0.
ModelScope@ModelScope2022AI score62AIInSpatio-World 1.5 from InSpatio_AI turns a single image, four images, a panorama, or a video into a navigable scene with wide viewpoint changes. The 1.3B model scores 68.72 on WorldScore-Dynamic, ranking first among evaluated real-time and interactive methods, with speeds up to 24 FPS. The post says the code is released under Apache 2.0 and that dependencies keep their own licenses.
AIKling 4.0 extends native single-pass video generation from 15 to 30 seconds and adds Multiple Keyframes supporting up to 10 keyframe images, versus Start & End Frames in Kling 3.0. It also expands reference inputs to up to 15 combined assets, including up to 5 videos totaling 30 seconds, and adds 10-bit HDR at 1080p and 4K. The all-new Kling 4.0 will officially launch in October, and Kling 4.0 Flash became available to a limited group of early-access users on September 28.
AIKorean AI lab Upstage has released Solar Mini 4, a proprietary reasoning model that scores 24 on the Artificial Analysis Intelligence Index with 35B total and 3B active parameters. It is priced at $0.10/$0.40 per 1M input/output tokens and has a 1M-token context window, but averages 7.1 minutes per task due to heavy output token use. Its weights are not released, and its size cannot be independently verified.
AIArtificial Analysis reports that Google's Gemini 4 Argon scores 53 on its Intelligence Index with high reasoning, matching GPT-6 Astra (max) and one point ahead of GPT-6.1 Sol (max). At the current 50% launch discount, its cost per task is $1.99, about 60% of GPT-6 Astra's $3.26, but the discount's end date is unconfirmed and standard pricing would raise it to $3.98. The model is being rolled out to selected users and is not publicly available.
Why it matters: The benchmark compares Gemini 4 Argon's cost per task and hallucination rate with GPT-6 Astra, showing where its value depends on a temporary 50% discount.
Liquid AI@liquidaiAI score32AILiquid AI announced d1, its first decision model, which it says is the first to outperform Jev on Hugging Face's Decision Index. The company claims d1 wins on multilingual evals, resists prompt injection better, handles longer inputs more effectively, and is built for fast, structured decision-making in software environments. It is available via the Liquid API at console.liquid.ai, with OpenRouter availability coming soon.
Sam Altman@samaAI score60AIOpenAI's Sam Altman introduces 6.1 Sol, a model with near-Astra intelligence priced at one fifth of Astra and a 95% cache read discount. The quoted post says ultrafast mode gives 8X speed for Astra today and will come to 6.1 Sol soon.
AIBAAI released AREX-2, a 27B-parameter long-horizon agent model that improves solutions over multiple test-time rounds by proposing, measuring, reflecting, and revising. It was trained on machine-learning and algorithmic-programming tasks with verifiable feedback, and the source reports that this self-improvement transfers to deep research. The model is Apache License 2.0 licensed and has a 262,144-token context length.
Why it matters: The source compares AREX-2 against closed and open models on coding and deep-research benchmarks, showing how test-time self-improvement is measured across task types.
OpenAI@OpenAIAI score62AIOpenAI says GPT-6.1 Sol is available starting today to all Plus, Pro, Business, Enterprise, and Edu users. The model is offered in ChatGPT Work and Codex, and the post links to OpenAI's introduction page.
OpenAI@OpenAIAI score37AIOpenAI reports that GPT-6.1 Sol shows major alignment improvements over GPT-6 Sol in its evaluations, moving closer to GPT-6 Astra. The model is more transparent about its limitations and more reliable at respecting user intent and safety constraints.
ModelScope@ModelScope2022AI score54AIModelScope announced IQuest-Q1, a 320B MoE model with 15B active parameters and a 512K context window for agentic coding. The post reports scores of 84.5 on CyberGym, 83.2 on Terminal-Bench 2.1, 64.6 on DeepSWE v1.1, and 63.0 on NL2Repo, and says weights are released under the IQuest-Q1 License.
ModelScope@ModelScope2022AI score44AIShanghai AI Laboratory's Intern-Decision family of 0.8B, 2B, and 4B multimodal models averages 79.38, 84.68, and 90.02 across seven decision benchmarks. Intern-Decision-4B scores 88.74, surpassing Jev while achieving better probability calibration. Reported mean latency is 33.98, 33.28, and 44.16 ms, versus 109.70 ms for Jev in the same local HF setup.
AIInternLM's AutoVerifier, built on Qwen3_5MoeForConditionalGeneration with about 68 GiB of weights across 40 safetensors shards, evaluates natural-language mathematical proofs, explains errors, and identifies the earliest incorrect step. It serves as the automatic grader for AdvancedMathBench's ProverBench, which accepts a proof only when all eight judgments report -1. The model is a learned grader rather than a formal proof checker and can make errors.
AIArtificial Analysis reports that GPT-6.1 Sol replaces GPT-6 Sol after seven days and scores 1 point below GPT-6 Astra on the Intelligence Index. At max effort it costs $0.72 per Intelligence Index task, compared with $3.26 for GPT-6 Astra and $1.05 for GPT-6 Sol. Its pricing matches GPT-6 Sol at $2/$10 per million input/output tokens, but it uses about 10-30% more output tokens.
Why it matters: The source compares GPT-6.1 Sol against GPT-6 Sol, GPT-5.6 Sol, and GPT-6 Astra on cost per task and token use, helping readers weigh performance against price.
ModelScope@ModelScope2022AI score44AIAudio8 ASR Infinite transcribes Chinese and English audio of unlimited length using a rolling KV Cache that avoids accumulated drift. At a 480 ms delay, it reports 1.75 CER on AISHELL-1, 2.89 on AISHELL-4, and 3.04/6.81 WER on LibriSpeech test-clean/test-other. The preview release is under Apache 2.0, with deployment through an adapted vLLM stack.
Mike Krieger@mikeykPickAI score67AIAnthropic has released Claude Sonnet 5.5, the second model in the Claude 5.5 family. The company says it is more than 30% faster than Sonnet 5 and costs up to 30% less for most work.
Why it matters: The post gives concrete speed and price changes against Sonnet 5, which helps readers judge whether the upgrade fits their workloads and budgets.
cat@_catwuPickAI score72AIAnthropic's Cat Wu says Claude Sonnet 5.5 lets Claude Code users complete about 30% more tasks than with Sonnet 5. The model needs fewer tokens for the same work, and in a leaf-raking tool-call demo it finished 24 seconds faster using 6K fewer tokens.
Why it matters: The post gives a measured Claude Code task-completion gain and a token-use example, showing what the model upgrade means for a coding agent workflow.
Boris Cherny@bchernyAI score38AIAnthropic's Claude Sonnet 5.5, the second model in the Claude 5.5 family, is shown fixing a bug in Claude Code. Boris Cherny says it runs 30% faster and uses 30% less usage, and Anthropic's announcement says it runs over 30% faster and costs up to 30% less for most work.
Felix Rieseberg@felixriesebergAI score58AIAnthropic launched Sonnet 5.5, which the post says is smarter and more tasteful than Sonnet 5. It is positioned for work that does not need the extra capability of Opus or Fable.
Anthropic@AnthropicAIAI score61AIAnthropic has released Claude Sonnet 5.5, the second model in the Claude 5.5 family. The quoted announcement says it is a clear upgrade over Sonnet 5, runs more than 30% faster, and costs up to 30% less for most work.
ModelScope@ModelScope2022AI score43AIJina-OCR-v1, a 3.4B-parameter MoE model that activates 570M parameters per token, converts entire document pages into structured Markdown at 2.57 pages per second. It scores 91.14 on OmniDocBench v1.6 and 83.4 on olmOCR-Bench, 7.4 points above DeepSeek-OCR on the latter, and delivers the highest throughput among 14 evaluated systems at concurrency 32. The model is released under CC BY-NC 4.0, so commercial use requires permission.
AIAnthropic has launched Claude Sonnet 5.5, the second model in its Claude 5.5 family. The company describes it as a faster, lower-cost complement to Claude Opus 5.5, and points readers to a blog post for more information.
Why it matters: The release note places Sonnet 5.5 beside Opus 5.5 in the Claude 5.5 family, clarifying which model suits speed and cost needs.
AIXiaomi has released MiMo-V2.6-Flash-MOPD on Hugging Face, an upgrade of the MiMo-V2.6-Flash-RL checkpoint that fuses several domain-specialized teachers into one model. The sparse MoE model has 309B total and 15B activated parameters, a 1M-token context length, and supports text, image, video, and audio inputs. The checkpoint targets tool-call repetition, a failure mode where the model repeatedly issues the same or similar tool calls without making progress.
AIXiaomi has released MiMo-V2.6-Pro-MOPD, an upgrade of the MiMo-V2.6-Pro-RL checkpoint that fuses several domain-specialized teachers into one model via MOPD2 and targets tool-call repetition. The sparse MoE model has 1.02T total and 42B activated parameters, a 1M-token context length, and accepts text, image, video, and audio inputs. Weights are available on Hugging Face and ModelScope, with deployment recipes for SGLang and vLLM.
AIShanghai AI Lab's InternLM released Intern-Decision-4B, a multimodal structured decision model fine-tuned from Qwen3.5-4B, which returns answer distributions for multiple questions in one forward pass. On its benchmark table it scores an average of 90.02 with a Brier score of 0.347 and an ECE of 0.065, and per-query latency averages 44.16 ms on a single RTX 4090. The model is available with a Python DecisionEngine inference interface.
AIShanghai AI Lab's InternLM released Intern-Decision-2B, a multimodal structured decision model fine-tuned from Qwen3.5-2B that returns calibrated answer distributions for multiple questions in one forward pass. It averages 84.68 across listed benchmarks with a 0.437 Brier score and 33.28 ms mean latency on a single RTX 4090. Model weights, a Python DecisionEngine API, and GitHub code are available, with support for up to 16 questions and eight images.
AIInternLM released Intern-Decision-0.8B, a multimodal structured decision model fine-tuned from Qwen3.5-0.8B that scores answers to multiple questions in one forward pass. The model reports a 79.38 average score and a 33.98 ms mean latency on a single RTX 4090, with 0.8B, 2B, and 4B sizes available. It is accessed through a Python DecisionEngine API that returns calibrated probabilities rather than generating free-form text.
Meituan LongCat@Meituan_LongCatAI score62AIMeituan's LongCat team has released LongCat-2.5-Preview, a natively multimodal model with 1.6T total parameters, about 48B active, and a 1M-token context window. The model is built for long-horizon tasks spanning terminals, browsers, GUIs, spreadsheets, and design tools. It is available now through an API on the LongCat platform and a chat interface.
ModelScope@ModelScope2022AI score23AIModelScope has released NeoHorse-Jev-4B, a compact open model that converts application states into structured decisions and probabilities. It scores 77.70 across six text decision benchmark groups, ranking first among four open-weight models with complete results in the comparison. Its prefill-only inference supports Choice, Noul, and Score primitives, accepts text or a single image with text, and is available under Apache 2.0 for deployment via vLLM, SGLang, Python, CLI, or HTTP.
Odyssey@odysseymlAI score38AIOdyssey introduced Agora-2, its next-generation multi-agent world model, which supports up to 20 humans and agents interacting in a shared environment simulated in real time. A multiplayer research preview is available to try now.
Philipp Schmid@_philschmidAI score22AIGoogle's Philipp Schmid announced Gemini 3.8 Flash, recommending Gemini for multimodal understanding. A quoted post by Spencer Schiff reported that frontier models struggled to match correct names to people in a drawing, offering a visual test for future models.
ModelScope@ModelScope2022AI score38AIModelScope released Qwen-Image-2.1-Fun-Controlnet-Union, a single checkpoint adding eight structural controls, including Canny, Depth, Pose, and Scribble, plus inpainting to Qwen-Image 2.1. Control and inpainting share one branch with 16 injection points across every second Transformer block, keeping the base model frozen and requiring no checkpoint switching. It runs at guidance scale 1.0 with CFG-distilled sampling and prefix KV caching, and is available under the Qwen Research License with base Qwen-Image 2.1 weights required.
SGLang@sgl_projectAI score23AIAlex Wortega releases openjev, a family of Jev-style models at 0.8B, 2B, 4B, and 35B-A3B for reranking, grading, guardrails, and real-time game decisions. The models come with SGLang serving support, according to the post.
Black Forest Labs@bfl_aiAI score32AIBlack Forest Labs says FLUX 3 Action can control a simulated drone to carry out a specific requested action. The post offers no further details on benchmarks, availability, or implementation.
Black Forest Labs@bfl_aiAI score40AIBlack Forest Labs says FLUX 3 Action takes recent camera frames, the system's current state, and a task description to return the next 32 actions. The model also predicts how the scene will change, and runs a continuous observe-plan-act-adjust loop. It can recover from its own mistakes, according to the company.
