# FastEmbed vs Nomic Embed

**Leader by vioscaleAI score:** FastEmbed

| Attribute | FastEmbed | Nomic Embed |
|---|---|---|
| **vioscaleAI score** | 56.9 (54% (medium)) | 42 (34% (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 AI platform purpose-built for architecture and construction professionals that automatically parses complex multimodal documents—including drawings, specifications, and project files—and provides intelligent agents for reviewing designs, checking compliance, and searching project knowledge. It is indexed under Embeddings Apis.","source":"https://nomic.ai","question":"What is Nomic Embed?","confidence":0.6},{"answer":"Nomic Embed offers a free tier, so you can start without paying. Paid plans start at $20 per month. Pricing changes often, so verify at source before relying on it.","source":"https://nomic.ai","question":"Is Nomic Embed free?","confidence":0.6},{"answer":"We have confirmed 7 integrations for Nomic Embed, including Autodesk Forma, Fieldwire, Bentley ProjectWise, Procore, SharePoint, Egnyte and ACC. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://nomic.ai","question":"What does Nomic Embed integrate with?","confidence":0.6},{"answer":"Nomic Embed is available worldwide. Its primary market is the United States.","source":"https://nomic.ai","question":"Where is Nomic Embed available?","confidence":0.5}]` |
| deployment.options | `{"cloud":true,"self_hosted":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. | Software platform that processes complex construction documents including drawings, specifications, and BIM models using AI to automate workflows such as drawing review, submittal management, and data extraction for architecture and construction teams. |
| 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}` | `{"architecture_model":"managed_cloud_api","multi_modal_image_and_text_joint_embeddings":true}` |
| integrations.count | 3 | 4 |
| integrations.list | `[{"name":"Qdrant"},{"name":"Langchain"},{"name":"Llama Index"}]` | `[{"name":"Autodesk Forma"},{"name":"Fieldwire"},{"name":"Bentley ProjectWise"},{"name":"Procore"},{"name":"SharePoint"},{"name":"Egnyte"},{"name":"ACC","native":true,"direction":"inbound"}]` |
| language.primary | Python | - |
| license.spdx | Apache-2.0 | - |
| market.availability | - | `{"primaryMarkets":["US"],"availabilityScope":"global","availableCountries":[],"notAvailableCountries":[]}` |
| pricing | `{"type":"open_source","freeTier":true,"sourceUrl":"https://qdrant.github.io/fastembed/","retrievedAt":"2026-09-13T20:06:10.444Z"}` | `{"type":"subscription","plans":[{"free":false,"name":"Self Service","summary":"$20/month","components":[{"kind":"fixed","amount":20,"period":"month","currency":"USD"}],"contactSales":false}],"summary":"From $20/month. Free tier available.","currency":"USD","freeTier":true,"sourceUrl":"https://nomic.ai","retrievedAt":"2026-09-06T16:22:46.870Z","startingPrice":{"amount":20,"period":"month","currency":"USD"},"billingPeriods":["month"]}` |
| pricing.free_tier | yes | yes |
| pricing.model | open_source | freemium |
| pricing.price_level | free | mid |
| pricing.starting_price | - | `{"amount":20,"currency":"USD"}` |
| 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 | Nomic Embed |
|---|:--:|:--:|
| **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: vioscaleAI. Generated 2026-10-16T20:10:20.170Z. "-" = undocumented, not absent.*