Google DeepMind released the Gemma 4 family of open-source models with multimodal capabilities (text, image, audio, video) and context windows up to 256K tokens. Four distinct model sizes—E2B (2.3B effective parameters), E4B (4.5B effective), 26B A4B (3.8B active), and 31B—are available under the Apache 2.0 license, with instruction-tuned and pre-trained variants.
April 2, 2026
Google DeepMind released the Gemma 4 family of open-weights multimodal models in four sizes: E2B (2.3B effective), E4B (4.5B effective), 26B A4B (25.2B total, 3.8B active), and 31B dense. All models support text and image input with 128K-256K context windows, reasoning modes, and native function calling for agentic workflows.
Google has released Gemma 4, a family of four open models ranging from 2B to 31B parameters, now available under the Apache 2.0 license for the first time. The 31B dense model ranks 3rd on the Arena AI Text Leaderboard, while the 26B mixture-of-experts variant ranks 6th, both outperforming significantly larger competitors. All models support multimodal inputs and are available on Hugging Face, Kaggle, and Ollama.
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.
Augment Code now offers Gemini 3.1 Pro alongside Claude Opus 4.6 and GPT-5.4. In head-to-head testing on structural refactoring tasks, Gemini matched or outperformed Opus while consuming 268 credits per task—46% cheaper than Opus's 488 credits—making it 2.6x more cost-effective per message in real-world usage.
Google has previewed Gemini Nano 4, a new on-device language model for Android, available now in early access via AICore Developer Preview. The model comes in two versions: Gemini Nano 4 Fast (3x faster than previous models, 60% less battery) and Gemini Nano 4 Full (higher reasoning capability). The models will launch on new flagship Android devices later this year.
Google DeepMind released the Gemma 4 family of open-weights models ranging from 2.3B to 31B parameters, featuring up to 256K token context windows and native support for text, image, video, and audio inputs. The flagship 31B model scores 85.2% on MMLU Pro and 89.2% on AIME 2026, with a smaller 26B MoE variant requiring only 3.8B active parameters for faster inference.
Microsoft AI released three foundational models on April 2: MAI-Transcribe-1 for speech-to-text across 25 languages, MAI-Voice-1 for audio generation, and MAI-Image-2 for video generation. The company positions these models as cheaper alternatives to Google and OpenAI offerings. Models are available on Microsoft Foundry with pricing starting at $0.36 per hour for transcription.
NVIDIA has optimized Google's Gemma 4 models for local deployment on RTX and Spark platforms, targeting the emerging wave of on-device agentic AI. The optimization enables small, efficient models to access real-time local context for autonomous decision-making without cloud dependency.
Microsoft has released MAI-Transcribe-1, a speech-to-text model that achieves the lowest word error rate on the FLEURS benchmark across 25 languages, outperforming Whisper-large-V3, GPT-Transcribe, and Gemini 3.1 Flash-Lite. The model runs 2.5 times faster than Microsoft's previous Azure Fast offering and costs $0.36 per audio hour.
Google DeepMind released Gemma 4, a family of four open models ranging from 2B to 31B parameters, all licensed under Apache 2.0. The 31B dense model ranks #3 on Arena AI's text leaderboard and the 26B mixture-of-experts variant ranks #6, outperforming closed models significantly larger in size.
MLCommons published MLPerf Inference v6.0 results on April 1, 2026, with Nvidia, AMD, and Intel each claiming top spots in different configurations. Nvidia's 288-GPU GB300-NVL72 system achieved 2.49 million tokens per second on DeepSeek-R1, while AMD's MI355X crossed one million tokens per second for the first time. Direct comparisons remain difficult as each chipmaker targets different market segments and benchmarks.
Alibaba has released Qwen3.6-Plus, its third proprietary AI model in days, featuring a 1 million token context window available via Alibaba Cloud Model Studio API. The model claims improved agentic coding capabilities and partially outperforms Anthropic's Claude 4.5 Opus in Alibaba-conducted benchmarks, though trails Claude 4.6 Opus released in December 2025.