{"ok":true,"source":"tensorfeed.ai","lastUpdated":"2026-04-30","count":18,"models":[{"id":"text-embedding-3-large","name":"text-embedding-3-large","provider":"OpenAI","type":"embedding","dimensions":3072,"maxInputTokens":8191,"pricePer1MTokens":0.13,"pricingNote":"$0.13 per 1M input tokens. Reducible-dimensions: pass `dimensions` to truncate to 256/1024/etc with minor quality loss.","openSource":false,"license":"Proprietary","released":"2024-01-25","notes":"OpenAI flagship embedding. Strong on English retrieval; supports Matryoshka truncation to lower dimensions for cheaper storage.","multilingual":true,"url":"https://platform.openai.com/docs/guides/embeddings","mtebAvg":64.6},{"id":"text-embedding-3-small","name":"text-embedding-3-small","provider":"OpenAI","type":"embedding","dimensions":1536,"maxInputTokens":8191,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens. The default budget choice for English RAG.","openSource":false,"license":"Proprietary","released":"2024-01-25","notes":"OpenAI budget embedding. 5x cheaper than ada-002 with better quality. Good default for most RAG agents.","multilingual":true,"url":"https://platform.openai.com/docs/guides/embeddings","mtebAvg":62.3},{"id":"voyage-3-large","name":"voyage-3-large","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.18,"pricingNote":"$0.18 per 1M input tokens. Recommended by Anthropic in the Claude docs.","openSource":false,"license":"Proprietary","released":"2025-01-07","notes":"Top of the MTEB English leaderboard most of 2025. Supports Matryoshka truncation. Strong on long-document retrieval.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":67},{"id":"voyage-3","name":"voyage-3","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.06,"pricingNote":"$0.06 per 1M input tokens. Best price/quality trade-off in the Voyage line.","openSource":false,"license":"Proprietary","released":"2024-09-18","notes":"Voyage workhorse. 32k context, multilingual, MTEB-competitive at a third the cost of voyage-3-large.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":63.5},{"id":"voyage-3-lite","name":"voyage-3-lite","provider":"Voyage AI","type":"embedding","dimensions":512,"maxInputTokens":32000,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens. Cheapest tier in the Voyage family.","openSource":false,"license":"Proprietary","released":"2024-09-18","notes":"Budget tier. 512-dim vectors keep storage costs low. Useful for very large corpora where retrieval recall matters less than ingest cost.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":60},{"id":"voyage-code-3","name":"voyage-code-3","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.18,"pricingNote":"$0.18 per 1M input tokens. Code-specialized.","openSource":false,"license":"Proprietary","released":"2024-12-05","notes":"Specialized for code-search agents. Strong on cross-language retrieval (e.g. natural-language query against a Python+Go+Rust monorepo).","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":null},{"id":"embed-multilingual-v3.0","name":"embed-multilingual-v3.0","provider":"Cohere","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens. 100+ languages.","openSource":false,"license":"Proprietary","released":"2023-11-02","notes":"Cohere multilingual flagship. 100+ languages with strong cross-lingual retrieval. Short input limit (512 tokens) is the main constraint.","multilingual":true,"url":"https://docs.cohere.com/docs/embeddings","mtebAvg":64},{"id":"embed-english-v3.0","name":"embed-english-v3.0","provider":"Cohere","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens.","openSource":false,"license":"Proprietary","released":"2023-11-02","notes":"English-only sibling of embed-multilingual-v3. Slightly stronger on English-only corpora.","multilingual":false,"url":"https://docs.cohere.com/docs/embeddings","mtebAvg":64.5},{"id":"gemini-embedding-001","name":"gemini-embedding-001","provider":"Google","type":"embedding","dimensions":3072,"maxInputTokens":2048,"pricePer1MTokens":0.15,"pricingNote":"$0.15 per 1M input tokens. Supports Matryoshka.","openSource":false,"license":"Proprietary","released":"2025-03-07","notes":"Google flagship embedding from the Gemini family. Strong multilingual. Available via Vertex AI and the Gemini API.","multilingual":true,"url":"https://ai.google.dev/gemini-api/docs/embeddings","mtebAvg":68.3},{"id":"text-embedding-005","name":"text-embedding-005","provider":"Google","type":"embedding","dimensions":768,"maxInputTokens":2048,"pricePer1MTokens":0.025,"pricingNote":"$0.025 per 1M input tokens. Vertex AI only.","openSource":false,"license":"Proprietary","released":"2024-11-14","notes":"Google budget tier. 768-dim, English-focused, cheapest of the Vertex AI embeddings.","multilingual":false,"url":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings","mtebAvg":null},{"id":"mistral-embed","name":"mistral-embed","provider":"Mistral","type":"embedding","dimensions":1024,"maxInputTokens":8000,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens via la Plateforme.","openSource":false,"license":"Proprietary","released":"2024-02-26","notes":"European data residency option. Solid English/French/German performance. Same pricing tier as Cohere but with longer context.","multilingual":true,"url":"https://docs.mistral.ai/capabilities/embeddings/","mtebAvg":60.7},{"id":"jina-embeddings-v3","name":"jina-embeddings-v3","provider":"Jina AI","type":"embedding","dimensions":1024,"maxInputTokens":8192,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens (Jina API). Free for self-hosting under Apache 2.0.","openSource":true,"license":"CC-BY-NC-4.0","released":"2024-09-18","notes":"Open-weights multilingual embedding. Strong on long documents. Adapter-based: same model serves retrieval, classification, separation tasks via task-specific LoRAs.","multilingual":true,"url":"https://jina.ai/embeddings/","mtebAvg":65.5},{"id":"nomic-embed-text-v1.5","name":"nomic-embed-text-v1.5","provider":"Nomic AI","type":"embedding","dimensions":768,"maxInputTokens":8192,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Hosted via Nomic Atlas at $0.01 per 1M tokens.","openSource":true,"license":"Apache-2.0","released":"2024-02-14","notes":"Open-source English embedding with Matryoshka support (truncate to 256/512/768). Reproducible training data; one of the few fully open embeddings.","multilingual":false,"url":"https://blog.nomic.ai/posts/nomic-embed-matryoshka","mtebAvg":62.3},{"id":"mxbai-embed-large-v1","name":"mxbai-embed-large-v1","provider":"Mixedbread","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Hosted via Mixedbread API at $0.05 per 1M tokens.","openSource":true,"license":"Apache-2.0","released":"2024-03-07","notes":"Apache-licensed dense retriever. Strong English performance. Short input limit (512) is the main constraint vs Voyage/Jina.","multilingual":false,"url":"https://www.mixedbread.com/docs/embeddings/overview","mtebAvg":64.7},{"id":"bge-m3","name":"bge-m3","provider":"BAAI","type":"embedding","dimensions":1024,"maxInputTokens":8192,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Available through most inference providers (Together, DeepInfra, Replicate).","openSource":true,"license":"MIT","released":"2024-01-30","notes":"Multi-functional, multi-lingual, multi-granularity. Outputs dense + sparse + multi-vector representations from a single model. Strong on long-document multilingual retrieval.","multilingual":true,"url":"https://huggingface.co/BAAI/bge-m3","mtebAvg":64.5},{"id":"rerank-v3.5","name":"rerank-v3.5","provider":"Cohere","type":"reranker","dimensions":null,"maxInputTokens":4096,"pricePer1MTokens":0,"pricingNote":"$2 per 1k searches (each search = up to 100 documents reranked).","openSource":false,"license":"Proprietary","released":"2024-12-03","notes":"Cohere flagship reranker. Strong multi-lingual reranking with 4k document context. The reranker that most production RAG agents are using as of 2026.","multilingual":true,"url":"https://docs.cohere.com/docs/rerank-2","mtebAvg":null},{"id":"rerank-2","name":"rerank-2","provider":"Voyage AI","type":"reranker","dimensions":null,"maxInputTokens":16000,"pricePer1MTokens":0.05,"pricingNote":"$0.05 per 1M tokens (query + documents combined).","openSource":false,"license":"Proprietary","released":"2024-08-09","notes":"Voyage reranker. 16k context per document is unusual; useful for reranking long-document chunks without summarization.","multilingual":true,"url":"https://docs.voyageai.com/docs/reranker","mtebAvg":null},{"id":"jina-reranker-v2","name":"jina-reranker-v2-base-multilingual","provider":"Jina AI","type":"reranker","dimensions":null,"maxInputTokens":1024,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M tokens via Jina API. Free to self-host.","openSource":true,"license":"CC-BY-NC-4.0","released":"2024-07-04","notes":"Open-weights reranker. 100+ languages. Smaller context than Cohere/Voyage but free to self-host.","multilingual":true,"url":"https://jina.ai/reranker/","mtebAvg":null}]}