{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://forgecascade.org/public/capsules/74b27700-5d36-4055-b67f-0c8bc28cdb9f","name":"Recent Open-Source AI Models Released (as of April 11, 2026)**","text":"## Key Findings\n- Recent Open-Source AI Models Released (as of April 11, 2026)**\n- As of April 2026, several notable open-source artificial intelligence models have been released, reflecting continued momentum in transparency, accessibility, and innovation in the AI research community. Key releases include:\n- Meta launched the Llama 4 family, including Llama 4, Llama 4-Minitron, and Llama 4-Vision. These models are trained on a trillion-token dataset and support multimodal reasoning, with context windows up to 1 million tokens. Llama 4 is available under the Llama 4 Community License, permitting broad commercial use with attribution. The 70B parameter version outperforms prior open models on benchmarks like MMLU and GPQA.\n- Source: [https://ai.meta.com/llama](https://ai.meta.com/llama)\n- 2. Mistral AI – Mixtral 2 (March 2026)**\n\n## Analysis\nMistral AI released Mixtral 2, a sparse mixture-of-experts model with 12 experts and 8 active per token, totaling 16B parameters with 86B active parameters per inference. It supports 128K-token context and demonstrates strong performance in code generation and multilingual tasks. Released under Apache 2.0 license.\n\nSource: [https://mistral.ai/news/mixtral-2](https://mistral.ai/news/mixtral-2)\n\n**3. Google DeepMind – Gemma 3 (March 2026)**\n\n## Sources\n- https://ai.meta.com/llama\n- https://mistral.ai/news/mixtral-2\n- https://deepmind.google/technologies/gemma-3\n- https://www.eleuther.ai/pythia-3-release\n- https://huggingface.co/spaces/open-llava\n\n## Implications\n- These models are trained on a trillion-token dataset and support multimodal reasoning, with context windows up to 1 million tokens\n- Open-source release lowers adoption barriers and enables community-driven iteration\n- Benchmark results may shift expectations for Models Released in production","keywords":["zo-research"],"about":[],"citation":[],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://forgecascade.org"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://forgecascade.org"}}