# FastEmbed vs Google Vertex AI Text Embeddings

**Leader by vioscaleAI score:** FastEmbed

| Attribute | FastEmbed | Google Vertex AI Text Embeddings |
|---|---|---|
| **vioscaleAI score** | 56.9 (54% (medium)) | 45.6 (35% (low)) |
| activity.commits_last_30d | 71 | - |
| adoption.dependent_repos | 4 | - |
| adoption.github_stars | 3,244 | - |
| content.faq | `[{"answer":"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. It is indexed under Embeddings Apis.","source":"https://qdrant.github.io/fastembed/","question":"What is FastEmbed?","confidence":0.6},{"answer":"Yes. FastEmbed can be deployed on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://qdrant.github.io/fastembed/","question":"Can FastEmbed be self-hosted?","confidence":0.6},{"answer":"Yes. FastEmbed is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/qdrant/fastembed","question":"Is FastEmbed open source?","confidence":0.95}]` | `[{"answer":"A cloud-based API that transforms text into high-dimensional vector embeddings using deep learning. Supports multiple languages and task types, integrating with vector databases for efficient semantic search. It is indexed under Embeddings Apis.","source":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings","question":"What is Google Vertex AI Text Embeddings?","confidence":0.6},{"answer":"We have confirmed browser-based access to Google Vertex AI Text Embeddings. That is the extent of what we could verify from public sources, so it may well offer desktop or mobile clients we have not indexed.","source":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings","question":"What platforms does Google Vertex AI Text Embeddings support?","confidence":0.6},{"answer":"We have only confirmed a cloud / SaaS deployment for Google Vertex AI Text Embeddings, so it appears to be vendor-hosted. If a self-hosted option exists we have not found it documented publicly.","source":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings","question":"Can Google Vertex AI Text Embeddings be self-hosted?","confidence":0.6},{"answer":"Google Vertex AI Text Embeddings is available worldwide. Its primary market is the United States.","source":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings","question":"Where is Google Vertex AI Text Embeddings available?","confidence":0.5}]` |
| deployment.options | `{"cloud":true,"self_hosted":true}` | `{"cloud":true}` |
| description.long | FastEmbed is a Python library that generates text and image embeddings using ONNX Runtime, eliminating the need for large PyTorch dependencies. It supports various embedding models including sparse embeddings, late-interaction models, and cross-encoders, making it suitable for serverless and resource-constrained environments. | A cloud-based API that transforms text into high-dimensional vector embeddings using deep learning. Supports multiple languages and task types, integrating with vector databases for efficient semantic search. |
| 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,"binary_and_scalar_quantization_for_memory_reduction":true,"task_specific_prefixes_query_vs_document_instructions":true}` | `{"pricing_model":"per_million_tokens_api","architecture_model":"managed_cloud_api","multi_modal_image_and_text_joint_embeddings":true,"massive_context_window_greater_than_8k_tokens":true,"multilingual_support_across_100_plus_languages":true,"task_specific_prefixes_query_vs_document_instructions":true}` |
| integrations.count | 3 | 1 |
| integrations.list | `[{"name":"Qdrant"},{"name":"Langchain"},{"name":"Llama Index"}]` | `[{"name":"Vector Search"}]` |
| language.primary | Python | - |
| license.spdx | Apache-2.0 | - |
| market.availability | - | `{"primaryMarkets":["US"],"availabilityScope":"global","availableCountries":[],"notAvailableCountries":[]}` |
| platform.support | - | `{"cli":true,"web":true}` |
| pricing | `{"type":"open_source","freeTier":true,"sourceUrl":"https://qdrant.github.io/fastembed/","retrievedAt":"2026-09-13T20:06:10.444Z"}` | `{"type":"usage","summary":"Usage-based pricing; new customers receive $300 in free credits","currency":"USD","freeTier":true,"sourceUrl":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings","retrievedAt":"2026-10-02T10:50:37.470Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | open_source | freemium |
| pricing.price_level | free | low |
| pricing.transparent | - | no |
| release.cadence_days | 33 | - |
| release.history | `[{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.9.0","date":"2026-10-07T16:39:40Z","type":"stable","version":"v0.9.0"},{"url":"https://github.com/qdrant/fastembed/releases/tag/v0.8.1","date":"2026-09-22T20:52:04Z","type":"stable","version":"v0.8.1"},{"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"}]` | - |
| security.vulnerabilities | `{"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 | FastEmbed | Google Vertex AI Text Embeddings |
|---|:--:|:--:|
| **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 | Per million tokens API |

*Source: vioscaleAI. Generated 2026-10-16T20:16:11.570Z. "-" = undocumented, not absent.*