What does AI recommend for embedding model apis and services?

Across 1,459 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 1,459 AI responses to this market's buyer questions over the last 30 days. Answers are collected daily and the ranking is re-measured on the same 30-day window.

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 25, 2026 · Based on 1,459 AI responses · Shares cover the last 30 days · 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	Microsoft		16%
13	Sentence-Transformers		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	LangChain		4%
31	Mistral		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	OpenSearch		2%
44	FAISS		2%
45	Mongodb		2%
46	ChemTEB		2%
47	Eden AI		2%
48	BES4RAG		2%
49	Replicate		2%
50	GreenNode AI		2%
51	Redis		2%
52	Databricks		2%
53	FastEmbed		2%
54	Nomic Embed Text v1		2%
55	MiniLM-L12-H384-uncased		2%
56	Datastax		2%
57	embedding-eval		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%