BGE Multilingual Gemma2
BGE Multilingual Gemma2 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 4k 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
No tracked provider token pricing is available yet.
About
BGE Multilingual Gemma2 is BAAI's large multilingual embedding model built on Google's Gemma 2 9B decoder architecture (42 layers, 3584 hidden dim). It supports instruction-based encoding for retrieval tasks and achieves state-of-the-art results on MIRACL, MTEB-pl, and MTEB-fr benchmarks, with strong performance across MTEB, C-MTEB, and AIR-Bench. It covers diverse languages including English, Chinese, Japanese, Korean, and French, and supports a 4,096-token context window.
BGE Multilingual Gemma2 is an open-source model in the BGE family. The structured metadata tracks a 4k-token context window. No headline benchmark score is tracked for BGE Multilingual Gemma2 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.
No tracked provider token pricing is available yet.