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Kyutai Releases REKI, a 2.4B Vision-Language-Action Model with Cached Register Memory

Kyutai, with Inria and École des Ponts, has released REKI, a 2.4B-parameter vision-language-action model for robot manipulation that was pretrained only on public data. It pairs a Qwen3.5-2B backbone with a 200M-parameter flow-matching action expert, and adds memory through 32 learned register tokens cached over the last three frames rather than feeding past frames into the VLM. The authors report 90.4% on LIBERO-Plus and 65.8% on RoboTwin Clean2Rand, with plain-language controls cutting arm oscillation on RoboTwin from 18.6% to 4.1%. Weights are on Hugging Face under CC BY-NC-SA 4.0, with six checkpoints including benchmark finetunes.

Why it matters: It offers a concrete, openly released VLA and a cheap memory design that robotics practitioners can inspect, reproduce and finetune.

MarkTechPost20h agoScore 81

Kyutaivision-language-action modelsrobot manipulation

Models

DeepSeek Releases V4.1-Flash-1017 Open-Weight Model and Opens Search APIs

DeepSeek has released V4.1-Flash-1017, an open-weight model that reports better benchmarks, faster task completion and shorter outputs than its predecessor. The company also opened its internal search engine through new Search and Fetch APIs priced at $0.75 per 1,000 calls, with free access for now for API users in tools such as Claude Code and Codex. The release targets agentic tasks at lower per-task cost.

The Decoder1d agoScore 73

DeepSeekopen-weight modelsAI agents

Products

Roundup of 20 decision-model alternatives to TypeSafe's Jev

MarkTechPost compares 20 decision models released within about four weeks of TypeSafe's Jev launch, spanning Cloudflare, OpenAI, Perplexity, Liquid AI, AWS's Strands Labs and independent developers. The guide lists size, license, input modalities, Jev API compatibility, pricing and reported benchmarks for each. Most figures are vendor-reported and per the article are not comparable across benchmark suites, while one third-party run from Respan keeps Jev ahead on accuracy but shows Tev1 4B better

MarkTechPost1d agoScore 72

decision modelsTypeSafeCloudflare

Industry

China Plans Export Controls on Open-Weight Models and 23 Key AI Technologies

China plans to restrict exports of 23 key AI technologies, including model weights, source code, and training methods for systems meeting thresholds of 10^26 FLOPs or 2 trillion parameters. A fast-track rule would still clear open-source releases once registered. The report suggests the move may push Western companies toward US open-weight models over Chinese alternatives.

The Decoder1d agoScore 78

China AI policyexport controlsopen-weight models

Models Editor selected

Reflection AI Releases Beam, a 501B-Parameter Open-Weight Model for Agentic Coding

Reflection AI has released Beam, an open-weight sparse mixture-of-experts model built for agentic coding and long-horizon software tasks. Beam has 501 billion total parameters with 23 billion active, a reported 1 million-token effective context length, and Apache 2.0 weights on Hugging Face in BF16, FP8 and NVFP4 checkpoints. The AWS post details deployment via SageMaker JumpStart real-time endpoints or SageMaker HyperPod Inference with JumpStart, SGLang or vLLM, including GPU sizing and tuning

Why it matters: It documents a new open-weight agentic coding model with concrete parameter counts, licensing and deployable AWS serving paths that developers can evaluate.

AWS Machine Learning Blog2d agoScore 82

Reflection AIBeamopen-weight models

Models

Meta launches open-weight Muse Spark Open model for Apple silicon

Meta has launched Muse Spark Open, a new open-weight AI model that runs locally on Apple silicon, in collaboration with Apple. The model is designed for on-device execution on Macs rather than requiring cloud inference. The source material does not specify model size, licensing terms, or performance benchmarks.

TechCrunch AI2d agoScore 70

MetaAppleopen-weight models

Models

Meta Releases Muse Spark Open, an 816B Open-Weight Multimodal Model

Meta has introduced Muse Spark Open, an open-weight model with 816 billion parameters that handles text, images, video and audio with context windows up to one million tokens. According to the report, it performs roughly on par with the most capable open-weight Chinese models on benchmarks and is optimized to run locally on Apple's M5 Ultra. The release positions Meta against Qwen, GLM and Kimi in the open-weight race.

The Decoder2d agoScore 78

Metaopen-weight modelsmultimodal AI

Products

Meta's Muse Spark Open coding model now deployable via Amazon SageMaker JumpStart

Meta's coding-optimized open-weight model Muse Spark Open is now available in Amazon SageMaker JumpStart, with BF16 and NVFP4 quantized variants. The MoE model has 816B total parameters (42B active), a 1M-token context window, and accepts text, image, document, audio, and audio-video input. It deploys to SageMaker AI endpoints in the user's own AWS account via Studio or the Python SDK, with VPC, KMS encryption, and network isolation options.

AWS Machine Learning Blog2d agoScore 76

MetaAmazon SageMakeropen-weight models

Models Editor selected

NVIDIA Expands Nemotron Family With Open Super VL and Bolt Models

NVIDIA released Nemotron 3.5 Super VL, an open 120-billion-parameter vision-language model aimed at multimodal agentic tasks such as tool use, instruction following and document understanding, along with open weights, datasets and training recipes. It also introduced two edge models, Nemotron 3.5 Bolt 74B-A9B 24GB for local agentic workloads and Bolt E4B 4GB for conversational and physical agents. Super VL and Bolt 74B-A9B are available now, with Bolt E4B due Oct. 23. NVIDIA says several organiz

Why it matters: It gives readers concrete details on three newly released open models spanning data center to edge, including deployment options, availability and enterprise customization efforts.

NVIDIA Blog3d agoScore 80

NVIDIANemotronopen-weight models