Uploaded May 2025 | Updated September 2026, 1 week ago
Bamba-9B is an inference-efficient Hybrid Mamba2 model trained by IBM, Princeton, CMU, and UIUC on completely open data.At inference time, the model demonstrates 2.5x throughput improvement and 2x latency speedup compared to standard transformers in vLLM. To foster community experimentation, the model is immediately available to use in transformers, vLLM, TRL, and llama.cpp. We’ve also release tuning, training, and extended pretraining recipes with a stateful data loader, and invite the community to further improve this model. Model architecture, artifacts and evaluations on @HuggingFace, here: huggingface.co/blog/bamba
Bamba-9B is an inference-efficient Hybrid Mamba2 model trained by IBM, Princeton, CMU, and UIUC on completely open data.At inference time, the model demonstrates 2.5x throughput improvement and 2x latency speedup compared to standard transformers in vLLM. To foster community experimentation, the model is immediately available to use in transformers, vLLM, TRL, and llama.cpp. We’ve also release tuning, training, and extended pretraining recipes with a stateful data loader, and invite the community to further improve this model. Model architecture, artifacts and evaluations on @HuggingFace, here: huggingface.co/blog/bamba
