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#Model release

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Sep 28

Sep 28Mon
  1. Ali GhodsiAI score62

    Databricks finds Opus 5.5 cheaper and better, GPT-6 Luna 20x cheaper per task

    AIDatabricks tested recent AI models across 2,400 engineers and found Opus 5.5 offers the highest quality mid-tier performance, with about 20% lower same-task costs than Opus 4.8. The company is now encouraging Opus 5.5 as a default model for coding, and reports that GPT-6 Luna is at least 20 times cheaper per task than Opus 5.5, roughly matching Opus 4.6 on one difficult evaluation suite. The Luna findings are preliminary.

  2. Mike KriegerAI score67

    Anthropic releases Claude Sonnet 5.5, 30% faster and up to 30% cheaper than Sonnet 5

    AIAnthropic 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.

  3. Cat WuAI score72

    Claude Sonnet 5.5 Lifts Claude Code Task Completion by About 30%

    AIAnthropic'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.

  4. ReplicateAI score28

    Pruna's P-Video-2-Pro video model now runs on Replicate

    AIReplicate has added P-Video-2-Pro, the latest video model from Pruna AI, which sits on the edge of the preference-speed and preference-price Pareto frontiers. Design Arena ranks its Quality and Speed variants tied for #2 on the Image to Video leaderboard with an Elo of 1325, with the Quality version generating in 8.0 seconds and the Speed version in 4.5 seconds.

  5. Google Cloud · AI & Machine LearningAI score40

    Why startups should pair open models like Gemma 4 with frontier APIs

    AIGoogle Cloud argues startups should combine open-weight models with frontier APIs rather than routing every request to one frontier model. It cites Gemma 4, which spans five sizes including a 31B dense model and a 26B A4B Mixture-of-Experts model, released under Apache 2.0. The article's examples report a 44% latency drop for Cue, from 876 ms to 488 ms, and a $0 server cost for BetterSpeak's on-device Gemma 4 E2B.

  6. ModelScopeAI score43

    Jina-OCR-v1 parses full pages into Markdown at 2.57 pages per second

    AIJina-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.

Sep 27

Sep 27Sun
  1. Claude Apps Release NotesAI score65

    Anthropic launches Claude Sonnet 5.5 as second Claude 5.5 model

    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.

  2. Amp NewsAI score67

    Amp switches its default medium mode to Claude Opus 5.5

    AIAmp now uses Claude Opus 5.5 for its medium mode by default, replacing GPT-5.6 Sol, while ChatGPT subscribers can keep medium pinned to GPT-5.6 Sol. In Amp's internal evals, Opus 5.5 solved 65% of tasks versus 61% for GPT-5.6 Sol and 56% for Opus 5, at lower cost, and it runs at high reasoning effort because xhigh and max cost more without scoring better.

    Why it matters: The source reports internal eval scores, cost comparisons, and usage guidance for choosing reasoning effort, helping developers decide which model and setting to run.

  3. MiniMaxAI score34

    MiniMax-M3.1 Flash Preview launches on Token Plan for high-volume teams

    AIMiniMax has made MiniMax-M3.1 Flash Preview available on its Token Plan, targeting teams with high-volume, latency-sensitive workloads. The model is faster and lighter, and it can be used under an existing Token Plan subscription without extra setup. MiniMax also says the text model, M3.1-Flash-Preview, debuted on MiniMax Code for everyday development tasks.

  4. Tibor BlahoAI score85

    OpenAI releases GPT-6 Sol and Luna as Anthropic launches Claude Opus 5.5

    AIOpenAI released GPT-6 Sol and Luna, priced 50 percent below GPT-5.6 promo API pricing, and rolling out in ChatGPT Work, Codex and the API, not yet in regular Chat. Anthropic released Claude Opus 5.5, described as roughly Claude Fable 5.1 level for 40 percent less than Opus 5 and over 30 percent faster, with Sonnet 5.5 and Haiku 5.5 due in coming weeks.

    Why it matters: The recap puts OpenAI and Anthropic releases side by side, with pricing and capability claims that help compare the two launches.

  5. Tibor BlahoAI score71

    OpenAI and Anthropic ship GPT-6 Sol and Luna and Claude Opus 5.5 in the same week

    AIOpenAI released GPT-6 Sol and Luna at API prices 50% below GPT-5.6 promotional pricing, and Anthropic released Claude Opus 5.5 the same day at 40% less than Opus 5. The roundup also covers Claude Code cloud sessions reaching general availability, the Claude Marketplace launch, OpenAI's new misalignment disclosures after the Hugging Face incident, and DevDay on September 29. The post is a relayed weekly digest, and it includes the author's closing promotion for AIPRM, which is not part of the reported news.

  6. The SequenceAI score55

    Opus 5.5 cuts costs while Meta and US–China talks widen AI's reach

    AIAnthropic released Claude Opus 5.5 at about 40% lower cost than Opus 5, priced at $4/$20 per MTok input/output. Meta said Muse is coming to its AI glasses in the coming months, while Washington and Beijing held their first AI dialogue and discussed an incident-notification channel. The newsletter argues that costs, interfaces, experiments, and diplomacy increasingly determine how much value AI creates.

  7. Xiaomi MiMo · new models on Hugging FaceAI score44

    Xiaomi releases MiMo-V2.6-Flash-MOPD, an upgraded MoE model with 1M context

    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.

  8. Xiaomi MiMoAI score62

    Xiaomi MiMo Explains Fixing Tool-Call Repetition in MiMo-V2.6 Models

    AIXiaomi MiMo reports that tool-call repetition in MiMo-V2.6 reached over 0.05% of responses across agent harnesses, causing stalled agents and wasted context. The team traced the cause to an RL flooding penalty set at 32 calls per turn, which missed smaller excess behavior, and replaced the approach with a specialized teacher distilled via MOPD. Repetition rates for both Pro and Flash dropped substantially, at roughly $90,000 versus an estimated $2.31 million for the alternative fix.

    Why it matters: The post traces an agent failure to a reward blind spot and compares the costs of two fixes, offering a transferable debugging method for RL-trained tool-calling models.

Sep 26

Sep 26Sat
  1. Xiaomi MiMo · new models on Hugging FaceAI score50

    Xiaomi releases MiMo-V2.6-Pro-MOPD, a 1.02T-parameter sparse MoE model

    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.

  2. InternLM (Shanghai AI Lab) · new models on Hugging FaceAI score45

    Intern-Decision-4B: Multimodal structured decision model from Qwen3.5-4B

    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.

  3. InternLM (Shanghai AI Lab) · new models on Hugging FaceAI score44

    Intern-Decision-2B: Structured Multi-Question Decision Model Fine-Tuned from Qwen3.5-2B

    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.

  4. InternLM (Shanghai AI Lab) · new models on Hugging FaceAI score46

    Intern-Decision-0.8B: InternLM's structured decision model on Hugging Face

    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.

Sep 25

Sep 25Fri
  1. Google AIAI score57

    Google AI lists weekly releases including Gemini 3.8 TTS, Live Avatar, and Project Suncatcher

    AIGoogle AI's weekly roundup lists Gemini 3.8 Flash TTS and Flash-Lite TTS as expressive audio generation models. It also announces Gemini 3.8 Live with Live Avatar for near real-time visual conversation and a Live Chat voice feature on the Gemini Notebook mobile app across about 100 languages. Project Suncatcher will launch a prototype satellite to test Google TPUs in orbit and explore solar-powered AI compute in space.

  2. Meituan LongCatAI score62

    Meituan LongCat-2.5-Preview Launches with 1.6T Parameters and 1M-Token Context

    AIMeituan'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.

  3. Anthropic ResearchAI score67

    Claude computes a nine-loop physics amplitude that experts had not reached

    AIAnthropic researchers used Claude Science to compute the nine-loop six-particle amplitude in planar N=4 super Yang-Mills, a toy-model result that physicist Lance Dixon checked. The work reportedly cost roughly one or two thousand dollars, with about $100 of compute for the bootstrap calculation, and a similar result was reached by Song He's group.

    Why it matters: The guest post shows a frontier physics calculation done with modest compute, which helps readers gauge what current AI can handle in research and what it still cannot.

Sep 24

Sep 24Thu
  1. ModelScopeAI score23

    NeoHorse-Jev-4B open model turns app states into structured decisions

    AIModelScope 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.

  2. Google · Gemini appAI score62

    Google launches Gemini 3.8 Live with Live Avatar for enterprises

    AIGoogle introduced Gemini 3.8 Live with Live Avatar, which adds a visual persona with lip-syncing and expressions to its live dialogue models. The feature is available in Gemini Enterprise and supports 97 languages, with custom avatars available through enterprise allowlisting. Google says all output is watermarked with SynthID.

    Why it matters: The post specifies enterprise availability, custom avatar allowlisting, and 97-language support, which clarifies who can use the feature and how far it reaches.

  3. Google Cloud · AI & Machine LearningAI score55

    Gemini 3.8 Live with Live Avatar becomes generally available in Gemini Enterprise

    AIGoogle says Gemini 3.8 Live with Live Avatar is now generally available in Gemini Enterprise, with US and EU endpoints, provisioned throughput, and enterprise compliance. Its video avatars use synchronized lip-syncing, custom avatars are limited to an allowlist, and generated audio and video carry SynthID watermarks. The model also understands and speaks 97 languages and can run tool calls in the background while the conversation continues.