- Released
- 8mo ago
- Size
- 7.4Bparameters
Ai2 fully open 7B model that mixes transformer attention with Gated DeltaNet linear recurrent layers.
How it compares
Frequently asked questions
Running locally
An estimated 5.7 GB at Q4, 9.6 GB at Q8 and 17.6 GB at FP16. All VRAM figures are estimates from the 7.4B parameter count, with weights plus about 15% and 0.5 GB for a short context.
Yes. A 24 GB GPU fits at FP16 (estimated 17.6 GB), a 16 GB or 12 GB GPU fits at Q8 (estimated 9.6 GB) and an 8 GB GPU fits at Q4 (estimated 5.7 GB).
Yes. Q4 needs an estimated 5.7 GB, and assuming macOS lets the GPU use about 75% of unified memory, the smallest common Mac memory size that fits is 8 GB.
Privacy and data
Yes, Olmo Hybrid 7B Instruct has open weights, so you can self-host it for full control of your data.
Capabilities and specs
No. Its input modalities are text only.
Quality and benchmarks
Qwen3.5 0.8B by Alibaba, Qwen3.5 2B by Alibaba and LFM2 24B A2B by Liquid AI. They are matched on model kind and release date, with no comparable price.
Qwen3.5 0.8BOlmo Hybrid 7B Instruct vs Qwen3.5 0.8BQwen3.5 2BOlmo Hybrid 7B Instruct vs Qwen3.5 2BLFM2 24B A2BOlmo Hybrid 7B Instruct vs LFM2 24B A2B
Licensing and access
Olmo Hybrid 7B Instruct is open weights, released under the Apache 2.0 license.
Yes. Its Apache 2.0 license is a permissive license that allows commercial use.
From the Hugging Face repository allenai/Olmo-Hybrid-Instruct-DPO-7B.
Basics
Ai2. It was released on March 5, 2026.
Yes, it is open weights.
Generated from Vertical Tabs data, updated November 3, 2026.





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