Mamba 2 780M
Mamba 2 780M has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 2k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- Mamba 2
- Released
- 2023-12-08
- Context
- 2k
- Parameters
- 780M
- Architecture
- Decoder Only
- Knowledge cutoff
- 2020
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
Mamba-2 780M is a cutting-edge large language model that enhances the capabilities of its predecessor with an innovative Structured State Space Model (SSM) architecture. This design enables efficient handling of long sequences while maintaining competitive performance against traditional transformers. It utilizes the Structured State Space Duality (SSD) technique to blend benefits of SSMs and attention mechanisms, allowing linear scaling and optimal memory use during inference. Mamba-2 780M is adept at tasks requiring processing of extensive data and excels in language and multimodal applications. Trained on 300 billion tokens from large datasets like the Pile and SlimPajama, it demonstrates formidable zero-shot performance. It's optimized for speed and hardware efficiency, though it might face challenges with short contexts and complexity in implementation.
Mamba 2 780M is a proprietary model in the Mamba 2 family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for Mamba 2 780M yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.