What does AI recommend for embedding model apis and services?

OpenAI remains the top-recommended provider for users seeking a simple, high-quality embedding API. However, the market is diversifying, with specialized challengers like Voyage AI and Nomic rising rapidly to compete on performance, while the conversation shifts from general APIs to specific open-source models and evaluation benchmarks.

Which embedding model apis and services brands appear most in AI answers?

Across 1,433 AI responses, OpenAI is mentioned most, named in 39% of them, followed by Alphabet (33%) and Cohere (28%).

How does Parse rank these brands?

Parse measures each brand's mention rate — the share of answers naming it — across 1,433 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.

How does a brand enter this ranking?

Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.

Best embedding model apis and services, according to AI

Data as of Aug 16, 2026 · Based on 1,433 AI responses · See how Parse measures this

Embedding Model APIs and Services

324 brands

ParseChatGPT + Google AI

Parse

https://parse.gl

Measured across ChatGPT & Google AI

Best Embedding Model APIs and Services, According to ChatGPT & Google AI | Parse

#	Brand	What AI says	Mention rate
1	OpenAIThe default choice for a simple, high-quality, and developer-friendly embedding API.	The default choice for a simple, high-quality, and developer-friendly embedding API.	39%
2	Alphabet		33%
3	CohereA leading commercial alternative, frequently cited for strong multilingual embedding capabilities.	A leading commercial alternative, frequently cited for strong multilingual embedding capabilities.	28%
4	Hugging FaceThe primary hub for finding, comparing, and deploying open-source embedding models.	The primary hub for finding, comparing, and deploying open-source embedding models.	27%
5	PineconeA top-cited managed vector database for enterprise-scale embedding search and storage.	A top-cited managed vector database for enterprise-scale embedding search and storage.	24%
6	MTEB (Massive Text Embedding Benchmark)The dominant, industry-standard framework for evaluating and comparing embedding models.	The dominant, industry-standard framework for evaluating and comparing embedding models.	20%
7	Voyage AIA fast-growing commercial challenger noted for top-tier accuracy on specialized domains.	A fast-growing commercial challenger noted for top-tier accuracy on specialized domains.	19%
8	NomicA rising open-source player recognized for efficient and high-performing text embeddings.	A rising open-source player recognized for efficient and high-performing text embeddings.	19%
9	Amazon		18%
10	intfloat/e5-small-v2		17%
11	Weaviate		16%
12	Sentence-Transformers		16%
13	Microsoft		16%
14	Milvus		12%
15	Jina AI		11%
16	Alibaba Group		10%
17	sentence-transformers/all-MiniLM-L6-v2		10%
18	BAAI		10%
19	BAAI BGE-M3		9%
20	Ragas		8%
21	Ollama		8%
22	Qdrant		7%
23	Zilliz		7%
24	CohereA leading commercial alternative, frequently cited for strong multilingual embedding capabilities.	A leading commercial alternative, frequently cited for strong multilingual embedding capabilities.	6%
25	arXiv		5%
26	Snowflake		5%
27	DeepEval		5%
28	Datavid		4%
29	Qwen-3		4%
30	Mistral		4%
31	LangChain		4%
32	NVIDIA		4%
33	TruLens		3%
34	Baseten		3%
35	Supermemory		3%
36	Arize AI		3%
37	BEIR		3%
38	Multilingual E5 Large		3%
39	Embeddings Evaluator		3%
40	BentoML		3%
41	Google Gemini API		3%
42	BAAI/bge-large-en-v1.5		2%
43	FAISS		2%
44	Mongodb		2%
45	OpenSearch		2%
46	ChemTEB		2%
47	Eden AI		2%
48	BES4RAG		2%
49	Replicate		2%
50	GreenNode AI		2%
51	Redis		2%
52	FastEmbed		2%
53	Nomic Embed Text v1		2%
54	MiniLM-L12-H384-uncased		2%
55	Datastax		2%
56	embedding-eval		2%
57	Databricks		2%
58	Elastic		2%
59	LlamaIndex		2%
60	Stella		2%
61	NomicA rising open-source player recognized for efficient and high-performing text embeddings.	A rising open-source player recognized for efficient and high-performing text embeddings.	1%
62	Llama-Embed-Nemotron 8B		1%
63	Chroma		1%
64	ZenML		1%
65	fastText		1%
66	Medium		1%
67	BytevalKit-Emb		1%
68	BAAI bge-en-icl		1%
69	RTEB		1%
70	Hugging Face Spaces — MTEB leaderboard		1%
71	Beijing Academy of Artificial Intelligence		1%
72	NLP Cloud		1%
73	Reddit		1%
74	WEFE		1%
75	Stanford University		1%
76	Deepset		1%
77	Embedding Sync		1%
78	Scikit-learn		1%
79	Anthropic		1%
80	Hugging Face Trainer API		1%
81	Tiger Data		1%
82	vLLM		1%
83	word2vec		<1%
84	Vectara		<1%
85	ONNX		<1%
86	ONNX Runtime		<1%
87	ULLME		<1%
88	Galileo Learn		<1%
89	Hume		<1%
90	PostgreSQL		<1%
91	pgvector		<1%
92	intfloat		<1%
93	EvalNE		<1%
94	MXBAI Embed Large v1		<1%
95	GitHub		<1%
96	MLflow		<1%
97	IBM		<1%
98	ACL Anthology		<1%
99	Confident AI		<1%
100	E5-mistral-7b-instruct		<1%