E5 is Microsoft’s open-weight embedding family, including the multilingual-E5 series widely used for retrieval across languages.
See all models from MicrosoftModels in family
2
Open weight
2
API only
0
Avg score
66.8
Top benchmark
76.8
STS
Total HF downloads
2.6M
Primary modality
Embedding
First release
Dec 2023
Latest release
Feb 2024
Every release in the E5 family, ranked by composite score across benchmarks, popularity, efficiency, and versatility.
| # | Model | Modality | Score | Params | Released |
|---|---|---|---|---|---|
| 1 | embedding | AA72.7 | — | Feb 2024 | |
| 2 | embedding | BB60.8 | 7.1B | Dec 2023 |
When each release shipped, newest first. Useful for tracking version cadence.
Dec 31
Composite grades across this family. Higher is better, blending benchmarks, popularity, and efficiency.
Models with downloadable weights, ranked by composite score.
| # | Model | Modality | Score | Params | Released |
|---|---|---|---|---|---|
| 1 | embedding | AA72.7 | — | Feb 2024 | |
| 2 | embedding | BB60.8 | 7.1B | Dec 2023 |
The E5 family is a series of AI models from Microsoft. This page lists every release in the family with its benchmark scores, parameter count, and hardware requirements.
By composite score, multilingual-e5-large-instruct is currently the top model in the family. For local inference, match the parameter count to your VRAM budget. For quality, pick the highest scorer that fits.
See the open-weight section above for models you can run locally. The API-only section lists closed releases that must be accessed through the provider’s API.
Spin up an instance in the cloud, or pick local hardware that fits.
Full Directory
Open the full directory to filter by hardware, capability, license, and benchmark score.
Or Browse by Provider
See every model from a lab side by side, with aggregate stats. Useful when you want a cross-family view of one provider.
