Olmo Hybrid
7B open model mixing transformers and linear RNNs
Olmo Hybrid launched on March 7, 2026 with 107 votes, #413 of 23,380 launches that month and more than 95% of that year's launches.
What it does
Olmo Hybrid is a fully open 7B model that combines transformer attention with linear RNN layers. Utilizing a 3:1 pattern of Gated DeltaNet to attention, it matches the accuracy of Olmo 3 on MMLU while using 49% fewer tokens.
Ai2, a non-profit research institute founded by Paul Allen, is committed to breakthrough AI to solve the world’s biggest problems.
Hybrid language models – architectures that mix transformer attention with linear recurrent layers – have been gaining momentum across the field, with recent efforts from projects like Samba, Nemotron-H, Qwen3-Next, Kimi Linear, and Qwen 3.5. By combining transformers' ability to recall precise details from earlier in a sequence with recurrent layers' efficiency at tracking evolving state, hybrids promise to be both more capable and cheaper to run at long context lengths. But the community has lacked consensus on whether the purported benefits of hybrid architectures justify the cost of scaling them up. Today we're releasing Olmo Hybrid , a new 7B-parameter fully open model family that…from allenai.org
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