BGE Reranker V2 M3
bge-reranker-v2-m3
Last refreshed 2026-05-22. Next refresh: weekly.
BGE Reranker V2 M3 is worth evaluating for general LLM work when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-05-22.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 8K context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Cheapest output
-
Novita AI per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-05-22
Researched today
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Novita AI | $0.010 | - | ServerlessPartial |
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.
About
BGE Reranker V2 M3 is BAAI's lightweight multilingual cross-encoder reranking model from the FlagEmbedding project, based on the BGE-M3 backbone. Accepts query-passage pairs and outputs direct relevance scores. Supports multi-lingual processing with 568 million parameters. Part of the BGE reranker v2 series released March 2024 alongside LLM-based rerankers.
BGE Reranker V2 M3 has a 8K-token context window.
Capabilities
No model capability flags are currently sourced.
