# BAAI FlagEmbedding vs Voyage AI

| Attribute | BAAI FlagEmbedding | Voyage AI |
|---|---|---|
| **Vioscale score** | 58.6 (27% (low)) | 41.6 (20% (low)) |
| activity.commits_last_30d | 13 | - |
| adoption.dependent_repos | 1 | - |
| adoption.github_stars | 12,086 | - |
| deployment.options | `{"cloud":true,"on_prem":true,"self_hosted":true}` | `{"cloud":true,"hybrid":true}` |
| description.long | A library of state-of-the-art embedding models supporting dense, lexical, and cross-encoder retrieval methods for text and image search, available as free and open-source software. | A platform providing advanced embedding and reranking models designed to improve search accuracy and quality in retrieval-augmented generation workflows with support for various data types and deployment scenarios. |
| features.capabilities | `{"pricing_model":"free_open_weights","architecture_model":"open_weights_local","cross_encoder_reranker_api_offered":true,"mit_or_apache_permissive_oss_license":true,"late_interaction_architecture_colbert_v2":true,"multi_modal_image_and_text_joint_embeddings":true,"massive_context_window_greater_than_8k_tokens":true,"multilingual_support_across_100_plus_languages":true}` | `{"architecture_model":"managed_cloud_api","cross_encoder_reranker_api_offered":true,"multi_modal_image_and_text_joint_embeddings":true,"massive_context_window_greater_than_8k_tokens":true,"multilingual_support_across_100_plus_languages":true}` |
| integrations.count | - | 2 |
| integrations.list | - | `[{"name":"vector databases"},{"name":"LLMs"}]` |
| language.primary | Python | - |
| license.spdx | MIT | - |
| platform.support | `{"cli":true,"web":true}` | - |
| pricing | `{"type":"open_source","summary":"Free and open source under MIT license","freeTier":true,"sourceUrl":"https://github.com/pricing","retrievedAt":"2026-08-21T11:06:33.625Z"}` | - |
| pricing.free_tier | yes | - |
| pricing.model | commercial | commercial |
| pricing.price_level | free | - |
| pricing.transparent | yes | - |
| release.cadence_days | 104 | - |
| release.history | `[{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.4.2","date":"2026-08-24T02:55:16Z","type":"stable","version":"v1.4.2"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.4.1","date":"2026-08-23T12:48:07Z","type":"stable","version":"v1.4.1"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.4.0","date":"2026-04-22T15:59:10Z","type":"stable","version":"v1.4.0"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.3.5","date":"2025-05-28T07:14:20Z","type":"stable","version":"v1.3.5"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.3.4","date":"2025-02-07T14:14:41Z","type":"stable","version":"v1.3.4"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/v1.3.2-BGE-Update","date":"2024-10-31T16:23:48Z","type":"stable","version":"v1.3.2-BGE-Update"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/BGE-M3%26Beacon","date":"2024-02-02T05:57:07Z","type":"stable","version":"BGE-M3&Beacon"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/lm-cocktail","date":"2023-11-24T09:22:50Z","type":"stable","version":"lm-cocktail"},{"url":"https://github.com/FlagOpen/FlagEmbedding/releases/tag/1.1","date":"2023-09-28T07:43:03Z","type":"stable","version":"1.1"}]` | - |
| security.soc2 | - | yes |
| security.vulnerabilities | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=flagembedding&per_page=100","last_12m":0,"max_severity":null}` | - |

## Capabilities (Embeddings Apis)

| Capability | BAAI FlagEmbedding | Voyage AI |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Architecture model | Open weights local | Managed cloud API |
| Matryoshka representation learning for dimension truncation | - | - |
| Multilingual support across 100 plus languages | ✓ | ✓ |
| Binary and scalar quantization for memory reduction | - | - |
| Cross encoder reranker API offered | ✓ | ✓ |
| Late interaction architecture colbert v2 | ✓ | - |
| Massive context window greater than 8k tokens | ✓ | ✓ |
| Multi modal image and text joint embeddings | ✓ | ✓ |
| Task specific prefixes query vs document instructions | - | - |
| Zero data retention training opt out enterprise | - | - |
| SOC2 type ii | - | - |
| Mit or apache permissive oss license | ✓ | - |
| Pricing model | Free open weights | - |

*Source: Vioscale. Generated 2026-09-01T15:20:17.990Z. "-" = undocumented, not absent.*