256k-context

Tencent has released Hy3-preview, a 295-billion-parameter Mixture-of-Experts model with 21 billion active parameters and a 256K context window. The model scores 76.28% on MATH and 34.86% on LiveCodeBench-v6, with particularly strong performance on coding agent tasks.

Google DeepMind released Gemma 4, an open-weights multimodal model family in four sizes (2.3B to 31B parameters) with context windows up to 256K tokens. All models support text and image input, with audio native to E2B and E4B variants. The Gemma 4 31B dense model scores 85.2% on MMLU Pro, 89.2% on AIME 2026, and 80.0% on LiveCodeBench—significant improvements over Gemma 3.

Google DeepMind has released Gemma 4 26B A4B, a free instruction-tuned Mixture-of-Experts model with 262,144 token context window and multimodal capabilities including text, images, and video input. Despite 25.2B total parameters, only 3.8B activate per token, delivering performance comparable to larger 31B models at reduced compute cost.

Google DeepMind has released Gemma 4 31B Instruct, a free 30.7-billion parameter model with a 256K token context window, multimodal text and image input capabilities, and native function calling. The model supports configurable reasoning mode and 140+ languages, with strong performance on coding and document understanding tasks under Apache 2.0 license.

Google DeepMind released Gemma 4, an open-weights multimodal model family in four sizes (E2B, E4B, 26B A4B, 31B) with context windows up to 256K tokens and native reasoning capabilities. The 26B A4B variant uses Mixture-of-Experts architecture with 3.8B active parameters for efficient inference. All models support text, image input and handle 140+ languages with Apache 2.0 licensing.

Google DeepMind has released Gemma 4 31B, a 30.7-billion-parameter multimodal model supporting text and image input. The model features a 262,144-token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages under Apache 2.0 license.

Kwaipilot released KAT-Coder-Pro V2, the latest model in its KAT-Coder series, on March 27, 2026. The model features a 256,000-token context window and is priced at $0.30 per million input tokens and $1.20 per million output tokens. It targets enterprise-grade software engineering with focus on multi-system coordination and web aesthetics generation.

NVIDIA Nemotron 3 Super, a hybrid Mixture of Experts model with 120B parameters and 12B active parameters, is now available as a fully managed model on Amazon Bedrock. The model supports up to 256K token context length and claims 5x higher throughput efficiency over the previous Nemotron Super and 2x higher accuracy on reasoning tasks.