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Wednesday42 items

  1. The DecoderModel releases
    AI score73

    Inception Releases Diffusion Language Model Mercury 3, Claiming Speeds Four to Eight Times Faster Than GPT-6 Luna

    Inception has released the diffusion language model Mercury 3, claiming it wins 8 of 12 benchmarks and runs four to eight times faster than GPT-6 Luna and Claude Haiku 5.5. In Inception's own testing, Mercury 3 scored 76.84 on IFBench, 15 points higher than GPT-6 Luna; it scored 51.08 on SWE-Bench Atlas, versus 33.33 and 32.26 for its competitors. Claude Haiku 5.5 led on the DeepSWE long-code test and long-text retrieval. The model generates 1,068 tokens per second on Nvidia GPUs, is priced at $0.20 per million input tokens and $0.70 per million output tokens, with a 50% discount during the launch period, and is now available on the Inception platform as well as OpenRouter, Baseten, and Vercel; there are currently no independent tests.

    #Model releases#Reasoning#English text is being prepared.

  8. Unite.AIModel releases
    AI score64

    NVIDIA Releases Nemotron 3.5 Series of Open Models, Covering Embedding, Reranking, and Document Parsing

    On October 21, 2026, NVIDIA expanded the Nemotron Retriever series, launching Nemotron 3.5 Embed (8B BF16, 1B BF16, 1B NVFP4), Nemotron 3.5 Rerank 8B BF16, and the 631-million-parameter Nemotron 3.5 Parse, aimed at multimodal retrieval and document processing for enterprise agent workflows. NVIDIA says that adding Rerank to the agent retrieval pipeline reduces the token cost per query by about 14% (with the 8B embedding model) and 13% (with the 1B model), respectively, while also improving retrieval accuracy. Parse scores 75.20 on ParseBench and processes 10.5 pages per second on a single H100; the open weights, data, and training recipes have been released on Hugging Face and can be deployed via NVIDIA NIM as well as Baseten, DeepInfra, and FriendliAI.

    #Model releases#RAG#Multimodal

  12. LeiphoneModel releases
    AI score83

    MiniMax M3.1 Flash released, tops Agent task evaluation

    MiniMax released M3.1 Flash and claimed the previously anonymous model Space Bunny; it ranked first in the Automation-Bench complex Agent task comparison, and tied for first with Opus 5 on BankerToolBench at 76.2%. Leiphone used the same 3D campus building task for a real-world test: MiniMax Code plus M3.1 Flash took 55.4 minutes, while OpenCode plus DeepSeek V4.1 Flash took about 121 minutes, with model costs for both around 6.5 yuan. Pricing is 1 yuan per million input Tokens, 4 yuan for output, and 0.1 yuan for cache reads, roughly half the input and output prices of the previous generation M3, with no peak/off-peak distinction all day.

    Same story · 19 reports

    #Model releases#Agents#English text is being prepared.

  16. QbitAIModel releases
    AI score60

    Memory Tensor Open-Sources MemT 1.0 Series Memory-Native Models

    Memory Tensor has open-sourced and released the MemT 1.0 series of memory-native models, including MemT-1.0-Nano with 36B parameters and 3B activated (based on Qwen3.6-35B-A3B) and MemT-1.0-Flash with 288B parameters and 17B activated (based on DeepSeek-V4-Flash), adding a memory computation pathway parallel to attention in selected Transformer modules. The team built a 34-billion-token memory training corpus, of which 20 billion tokens were used for continued pre-training and 14 billion for post-training. In a comprehensive evaluation across 11 memory benchmarks, Flash and Nano achieved average scores of 50.6 and 47.0, respectively, ranking in the top two among the parametric memory methods evaluated; on 500 SWE-bench Verified tasks, the proportion of tasks that Nano succeeded on all three attempts rose from 54.00% for the no-experience baseline to 62.80%.

    Same story · 3 reports

    #Model releases#Open-source ecosystem#English text is being prepared.

  17. QbitAIModel releases
    AI score82

    MiniMax Releases M3.1 Flash Model, ALE Score of 29.6% Ranks First Among Domestic Models

    MiniMax officially released M3.1 Flash, formerly known as Space Bunny (Yutu), which previously topped the charts anonymously on OpenRouter. The model scores 29.6% on Agents' Last Exam, ranking first among domestic models, and scores 43 on the AA leaderboard; it achieves 73.7% on DeepSWE v1.1, 82.2 points on CyberGym, 76.2 points on BankerToolBench, tying for first with Claude Opus 5, and 61.7 points on OSWorld V2. The model adopts a sparse attention architecture, with output speeds of up to 200+ TPS and a median of 170+ TPS, input at 1 yuan per million tokens, output at 4 yuan, and cache reads at 0.1 yuan, with comprehensive usage costs reduced by 70% compared to the previous generation M3.

    Same story · 19 reports

    #Model releases#Agents#English text is being prepared.

  18. Titanium Media · AGIModel releases
    AI score78

    MiniMax Releases M3.1 Flash, Tested Frontend Coding Capabilities

    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.

    Same story · 19 reports

    #Model releases#English text is being prepared.#Open-source ecosystem