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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.

MarkTechPost21h agoScore 81

Kyutaivision-language-action modelsrobot manipulation

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StepFun Releases Step 5 Preview Open Weights: 600B MoE, 27B Active, 1M Context

StepFun has published open FP8 and BF16 checkpoints for Step 5 Preview, a sparse Mixture-of-Experts model with 600B total parameters, 27B active per token and up to 1M tokens of context, targeting long-horizon agentic work. The release lists data-center-only self-hosting requirements, including 4x B300 or 8x H200 GPUs for the FP8 checkpoint, and an API priced at $1.00 per 1M input tokens and $2.70 per 1M output tokens. StepFun-reported results put it near GLM-5.3 and Kimi K3 on DeepSWE v1.1, whi

Why it matters: It gives developers a concrete new self-hostable open-weight option for agentic and long-context work, with clear hardware requirements, pricing and benchmark caveats.

MarkTechPost1d agoScore 81

StepFunopen-weight LLMsmixture-of-experts

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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

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Meta Releases Muse Spark Open: 816B Open-Weight Multimodal MoE With 1M Context

Meta Superintelligence Labs released Muse Spark Open, an 816B-parameter Mixture-of-Experts model that activates 42B parameters per token and accepts text, image, video and audio input with a 1M-token context window. Weights ship in BF16 and NVFP4 on Hugging Face, with day-one support in SGLang, vLLM, TensorRT-LLM, Transformers, MLX, llama.cpp and Unsloth. Meta reports top scores on tool use (MCP-Atlas 89.2) but trails Kimi K3 and GLM 5.3 on Terminal-Bench 2.1 (76.4) and on Artificial Analysis In

Why it matters: It gives developers concrete open-weight release details, deployment options, license terms and comparative benchmark results for a large multimodal model they could actually adopt.

MarkTechPost2d agoScore 85

Meta Superintelligence LabsMuse Spark Openopen-weight LLMs

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NVIDIA Releases Nemotron 3.5 Super VL, a 120B Open Multimodal Agent Model

NVIDIA released Nemotron 3.5 Super VL, an open vision-language agent model with 120B total parameters and 12B active per token in a mixture-of-experts design, supporting text, image, document and video input with up to 1M-token context. It ships with an NVFP4 checkpoint runnable on a single DGX Spark, H200 or GB200, plus open datasets, training recipes and RL environments in NeMo Gym under the OpenMDW-1.1 license. NVIDIA-reported results include 89.90 on GPQA-Diamond and 71.07 on SWE-bench Verif

Why it matters: Developers get a concrete, deployable open multimodal agent model with published weights, licensing, hardware requirements and benchmark numbers to weigh against alternatives.

MarkTechPost2d agoScore 85

NVIDIANemotron 3.5open-weight LLMs

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Black Forest Labs releases open-weights FLUX 3 Image Klein image model

Black Forest Labs has released FLUX 3 Image Klein, a 5.6-billion-parameter open-weights image model with native 4K generation, pixel-precise editing and support for up to ten reference images. It runs on consumer GPUs with as little as 8 GB of VRAM and has 38 percent fewer parameters than its predecessor. The company says internal tests show it outperforming proprietary competitors.

Why it matters: An open-weights image model that runs on low-end consumer GPUs is directly useful to developers and creators building local image generation workflows.

The Decoder3d agoScore 80

Black Forest LabsFLUX 3 Image Kleinopen-weights image models

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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

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Meet Grok Voice 3.0: SpaceXAI Voice Agent Model Ranks #1 on Artificial Analysis

SpaceXAI released Grok Voice 3.0, an API-only real-time speech-to-speech voice agent model. It ranks first on the Artificial Analysis Speech-to-Speech Index with a score of 86.9 and achieves a 0.81-second time to first audio. The model maintains the prior $0.08-per-minute pricing and offers OpenAI Realtime API compatibility for developers.

Why it matters: Offers developers concrete benchmark data and deployment details for a top-ranked real-time voice agent model.

MarkTechPost3d agoScore 81

Grok Voice 3.0Artificial Analysis Speech-to-Speech Indexvoice agents

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Fish Audio Releases Drama 3, a 35B Open-Weight MoE Text-to-Speech Model

Fish Audio released Drama 3, a 35B mixture-of-experts text-to-speech model with about 3B active parameters per token, built on a Qwen3.5-35B-A3B backbone. It accepts plain-language acting directions, paired tags, and up to 16 speakers per request across 83 languages, with weights on Hugging Face and availability via the Fish Audio API. Self-hosting requires a single NVIDIA GPU with at least 48 GB in FP8 using SGLang-Omni, which supports only Hopper GPUs. It scores 93.2% overall on Artificial Ana

Why it matters: Developers evaluating open-weight TTS get concrete architecture, hardware, benchmark, pricing, and licensing details to decide between self-hosting and the hosted API.

MarkTechPost3d agoScore 83

Fish Audio Drama 3open-weight TTS modelsQwen3.5-35B-A3B

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Liquid AI Releases LFM2.5-24B-A2B: A 2B-Active MoE for On-Device Agents

Liquid AI released LFM2.5-24B-A2B, an open-weight 24B-parameter Mixture-of-Experts reasoning model with about 2B active parameters and 131,072-token context, targeted at local agent loops. It runs via GGUF/MLX on laptops and mini PCs, with cited speeds of 184 tokens/s on Apple M5 Max and 114 tokens/s on AMD Ryzen AI Max+ 395, plus single NVIDIA B300 serving. Liquid AI reports it leads or matches larger MoEs on several agentic, tool-use and instruction-following benchmarks, while trailing Qwen3.6

Why it matters: Provides a concrete open-weight release with on-device performance, agentic benchmark comparisons, licensing and deployment details useful for evaluating local agent models.

MarkTechPost4d agoScore 82

Liquid AILFM2.5Mixture-of-Experts

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Google Releases Gemini 4 Argon API With 1M Token Output Limit

Google DeepMind made Gemini 4 Argon generally available to developers, enterprises, and paid Gemini subscribers through the Gemini API, AI Studio, and Gemini platform. Argon is a proprietary sparse mixture-of-experts frontier model with native text, image, audio, and video input, and it supports up to 1M tokens for combined input and output, including responses up to 1M tokens. Introductory API pricing is $2 per million input tokens and $10 per million output tokens, rising to $4/$20 after Novem

Why it matters: This is a major frontier-model API release with a notable long-output capability, concrete pricing, benchmark results, and caveats that matter to developers choosing between leading models.

MarkTechPost4d agoScore 89

Gemini 4 ArgonGoogle DeepMindFrontier AI models

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llm-gemini 0.35 adds support for Gemini 4 Argon

Simon Willison released llm-gemini 0.35, adding support for Google's new Gemini 4 Argon model, available via the Gemini API and a $100/month subscription. At launch, Argon is priced at $2 per million input tokens and $10 per million output tokens, with a planned price doubling on December 1st. Artificial Analysis data shows Argon costing $2,407 to run their benchmark, placing it close to GLM-5.3 and cheaper than recent models from OpenAI, Anthropic, and Meta. The post also includes SVG generatio

Why it matters: Provides developers with timely, concrete details on a new Gemini model's pricing, benchmark cost, and real-world performance for model selection.

Simon Willison4d agoScore 83

Gemini 4 ArgonGoogleLLM pricing

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Cloudflare Releases Clef-omni, a 30B-A3B Multimodal Decision Model

Cloudflare released Clef-omni, an open-weight Apache-2.0 decision model that scores text, images, audio and video in a single call. It is post-trained from Qwen3-Omni-30B-A3B-Instruct as a 30B-total/3B-active MoE with 64,000-token context on Workers AI, priced at $0.15 per million tokens. Cloudflare reports strong intent classification results (97.7 macro-F1 on CLINC150+OOS) but weaker scores than text-focused Clef on reasoning and workflow evals, and Cloudflare's benchmark numbers were not inde

Why it matters: It documents a concrete new open-weight multimodal model release with architecture, pricing, latency and benchmark details useful for developers building multimodal agent pipelines.

MarkTechPost6d agoScore 85

Cloudflaremultimodal AI modelsMixture-of-Experts