# BAAI FlagEmbedding vs FastEmbed

| Attribute | BAAI FlagEmbedding | FastEmbed |
|---|---|---|
| **Vioscale score** | 58.6 (27% (low)) | 46.6 (31% (low)) |
| activity.commits_last_30d | 13 | 13 |
| adoption.dependent_repos | 1 | 4 |
| adoption.github_stars | 12,086 | 3,166 |
| deployment.options | `{"cloud":true,"on_prem":true,"self_hosted":true}` | `{"on_prem":true,"self_hosted":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 Python library that creates vector embeddings from text and images using efficient, quantized model weights optimized for speed and local inference. Supports multiple embedding architectures including multilingual models and outperforms OpenAI's Ada-002 in accuracy. |
| 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}` | `{"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,"binary_and_scalar_quantization_for_memory_reduction":true,"task_specific_prefixes_query_vs_document_instructions":true}` |
| integrations.count | - | 1 |
| integrations.list | - | `[{"name":"Qdrant"}]` |
| language.primary | Python | Python |
| license.spdx | MIT | Apache-2.0 |
| 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 | - |
| pricing.price_level | free | - |
| pricing.transparent | yes | - |
| release.cadence_days | 104 | 33 |
| 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"}]` | `[{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.8.0","date":"2026-03-23T17:14:03Z","type":"stable","version":"v0.8.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.7.4","date":"2025-12-05T12:18:02Z","type":"stable","version":"v0.7.4"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.7.2","date":"2025-08-25T15:05:56Z","type":"stable","version":"v0.7.2"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.7.1","date":"2025-06-16T09:06:43Z","type":"stable","version":"v0.7.1"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.7.0","date":"2025-05-13T14:32:19Z","type":"stable","version":"v0.7.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.6.1","date":"2025-04-10T13:51:36Z","type":"stable","version":"v0.6.1"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.6.0","date":"2025-02-26T13:55:32Z","type":"stable","version":"v0.6.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.5.1","date":"2025-01-20T10:43:31Z","type":"stable","version":"v0.5.1"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.5.0","date":"2024-12-24T19:53:25Z","type":"stable","version":"v0.5.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.4.2","date":"2024-11-13T13:41:59Z","type":"stable","version":"v0.4.2"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.4.1","date":"2024-10-21T20:30:12Z","type":"stable","version":"v0.4.1"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.4.0","date":"2024-10-21T18:19:56Z","type":"stable","version":"v0.4.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.3.5","date":"2024-08-23T18:16:09Z","type":"stable","version":"v0.3.5"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.3.4","date":"2024-07-17T15:31:05Z","type":"stable","version":"v0.3.4"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.3.1","date":"2024-06-17T18:05:55Z","type":"stable","version":"v0.3.1"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.3.0","date":"2024-06-05T17:11:17Z","type":"stable","version":"v0.3.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.2.7","date":"2024-05-03T19:56:28Z","type":"stable","version":"v0.2.7"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.2.6","date":"2024-04-01T15:30:37Z","type":"stable","version":"v0.2.6"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.2.5","date":"2024-03-20T13:44:11Z","type":"stable","version":"v0.2.5"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.2.4","date":"2024-03-13T18:26:53Z","type":"stable","version":"v0.2.4"}]` |
| 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}` | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=fastembed&per_page=100","last_12m":0,"max_severity":null}` |

## Capabilities (Embeddings Apis)

| Capability | BAAI FlagEmbedding | FastEmbed |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Architecture model | Open weights local | Open weights local |
| 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 | Free open weights |

*Source: Vioscale. Generated 2026-09-01T14:25:15.396Z. "-" = undocumented, not absent.*