1024-dimension embeddings trained on 94 languages, and the most-cited multilingual retrieval baseline outside BGE. Pick it against bge-m3 when the corpus is short-chunk and the comparison is cross-language recall rather than window size.
Modalities
Text → Text
Usage
How much this model is actually called here.
Rank
#74
of 98 active models
Tokens served
63.6K
all-time
Platform share
0.0%
of all tokens
Pricing
Pay per token. Cached input bills at this model’s own cached rate, listed below.
+ Estimate your workload− Estimate your workload
Estimated monthly cost
$0.8100
$0.0270 / day on Multilingual E5 Large
Same workload on:
Estimates use list pricing. Actual bills depend on real token counts, and every response includes its exact cost.
How it compares
Against the peers people actually weigh it against.
| Spec | Multilingual E5 Large | EmbeddingGemma 300M | BGE-M3 |
|---|---|---|---|
| Input /1M | $0.0135 | $0.0027 | $0.0135 |
| Output /1M | $0.00 | $0.00 | $0.00 |
| Context | 1K | 2K | 8K |
| Tools | No | No | No |
| Reasoning | No | No | No |
| Throughput | 460 tok/s | 1211 tok/s | 1318 tok/s |
Quick start
Up and running in under two minutes.
- 1
Create an API key
Sign up and grab a key from the dashboard — $0.50 free credit on the free tier, which covers Multilingual E5 Large. No card required.
Get API key → - 2
Make your first request
Submit a generation job and poll until it succeeds.
curl https://kymaapi.com/v1/embeddings \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "multilingual-e5-large", "input": ["first document", "second document"] }'
FAQ
Common questions about this model.