Agent frameworks in OpenAI model API answers

As of

All 16 companies by OpenAI recommendation prompt presence

LangGraph / Deep Agents leads at 37.5%; the middle of the board sits at 6.3%.

Ahead of second place: 12.5%
Held by the top three: 54%
Middle of the board: 6.3%
Below half the leader: 12 of 16

Rank, name and OpenAI recommendation prompt presenceMiddle 6.3%

1LangGraph / Deep Agents37.5%
2CrewAI25.0%
3Microsoft Agent Framework25.0%
4Haystack25.0%
5Mastra12.5%
6LlamaIndex12.5%
7Pydantic AI12.5%
8Vercel AI SDK12.5%
9Google Agent Development Kit0.0%
10DSPy0.0%
11OpenAI Agents SDK0.0%
12Hugging Face smolagents0.0%
13Strands Agents0.0%
14Agno0.0%
15BeeAI Framework0.0%
16Claude Agent SDK0.0%

The prompt boards are re-run in rotation, about one category a day, so each board refreshes every few weeks and shows the date of its snapshot.

8 checks behind each row · 100% confidence across rows.

Agent Frameworks brands in OpenAI model API answers current rankings
Rank	Name	OpenAI recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	LangGraph / Deep Agents	37.5%	36.11% · 13 / 36	25.49% · 13 / 51	36.36% · 12 / 33	1	This rank My rank
02	CrewAI	25.0%	22.22% · 8 / 36	15.69% · 8 / 51	0% · 0 / 33	1	This rank My rank
03	Microsoft Agent Framework	25.0%	13.89% · 5 / 36	9.8% · 5 / 51	18.18% · 6 / 33	1	This rank My rank
04	Haystack	25.0%	11.11% · 4 / 36	7.84% · 4 / 51	0% · 0 / 33	2	Showing My rank
05	Mastra	12.5%	16.67% · 6 / 36	11.76% · 6 / 51	12.12% · 4 / 33	3	This rank My rank
06	LlamaIndex	12.5%	11.11% · 4 / 36	7.84% · 4 / 51	3.03% · 1 / 33	1	This rank My rank
07	Pydantic AI	12.5%	8.33% · 3 / 36	5.88% · 3 / 51	6.06% · 2 / 33	2	This rank My rank
08	Vercel AI SDK	12.5%	5.56% · 2 / 36	3.92% · 2 / 51	18.18% · 6 / 33	1	This rank My rank
09	Google Agent Development Kit	0.0%	5.56% · 2 / 36	3.92% · 2 / 51	6.06% · 2 / 33	1	This rank My rank
10	DSPy	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	2	This rank My rank
11	OpenAI Agents SDK	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	8	This rank My rank
12	Hugging Face smolagents	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	1	This rank My rank
13	Strands Agents	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	3	This rank My rank
14	Agno	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank
15	BeeAI Framework	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank
16	Claude Agent SDK	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank

8 checks behind each row · 100% confidence across rows.

Agent Frameworks brands in OpenAI model API answers current rankings
Rank	Name	OpenAI recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	LangGraph / Deep Agents	37.5%	36.11% · 13 / 36	25.49% · 13 / 51	36.36% · 12 / 33	1	This rank My rank
02	CrewAI	25.0%	22.22% · 8 / 36	15.69% · 8 / 51	0% · 0 / 33	1	This rank My rank
03	Microsoft Agent Framework	25.0%	13.89% · 5 / 36	9.8% · 5 / 51	18.18% · 6 / 33	1	This rank My rank
04	Haystack	25.0%	11.11% · 4 / 36	7.84% · 4 / 51	0% · 0 / 33	2	Showing My rank
05	Mastra	12.5%	16.67% · 6 / 36	11.76% · 6 / 51	12.12% · 4 / 33	3	This rank My rank
06	LlamaIndex	12.5%	11.11% · 4 / 36	7.84% · 4 / 51	3.03% · 1 / 33	1	This rank My rank
07	Pydantic AI	12.5%	8.33% · 3 / 36	5.88% · 3 / 51	6.06% · 2 / 33	2	This rank My rank
08	Vercel AI SDK	12.5%	5.56% · 2 / 36	3.92% · 2 / 51	18.18% · 6 / 33	1	This rank My rank
09	Google Agent Development Kit	0.0%	5.56% · 2 / 36	3.92% · 2 / 51	6.06% · 2 / 33	1	This rank My rank
10	DSPy	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	2	This rank My rank
11	OpenAI Agents SDK	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	8	This rank My rank
12	Hugging Face smolagents	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	1	This rank My rank
13	Strands Agents	0.0%	2.78% · 1 / 36	1.96% · 1 / 51	0% · 0 / 33	3	This rank My rank
14	Agno	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank
15	BeeAI Framework	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank
16	Claude Agent SDK	0.0%	0% · 0 / 36	0% · 0 / 51	0% · 0 / 33	1	This rank My rank

Primary brandQuestion typeModel APIQuestion contains

Run a question live

36.1%

of these answers name or cite LangGraph / Deep Agents

13 of 36 answers

72.2%

Its share of the compared brands' appearances

10

Answers citing its own site

12 links to its domains

3 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
LangGraph / Deep Agentslangchain.com	36.1%13 of 36	Primary	72.2%	22	10	12	3 of 3
LlamaIndexllamaindex.ai	11.1%4 of 36	-25.0 pts	22.2%	12	1	1	3 of 3
OpenAI Agents SDKopenai.com	2.8%1 of 36	-33.3 pts	5.6%	1	0	0	1 of 3
Claude Agent SDKanthropic.com	0.0%0 of 36	-36.1 pts	0.0%	0	0	0	0 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01What are the best open-source frameworks for building reliable AI agents in a production application?Recommendation	LangGraph / Deep Agents, cited 1 4 sources`f736fd64`	None named 0 sources`a6011974`	LangGraph / Deep Agents, cited 1OpenAI Agents SDK 6 sources`30488435`
02Recommend a Python-first agent framework with typed dependencies, structured outputs, tool validation, and testability.Recommendation	None named 6 sources`0a93806d`	LangGraph / Deep Agents 5 sources`c99bde45`	None named 5 sources`8ec5300a`
03Which TypeScript toolkit is best for streaming agent interfaces, tool calling, structured data, and multiple model providers?Recommendation	None named 8 sources`dda87429`	None named 0 sources`f09a530c`	None named 7 sources`aedcdcf7`
04Recommend a framework for role-based multi-agent teams, explicit handoffs, delegation, and human approval steps.Recommendation	None named 8 sources`6b63d488`	None named 0 sources`84227f68`	LangGraph / Deep Agents, cited 1 8 sources`23fecae1`
05What is the best framework for durable stateful agent graphs with checkpointing, retries, memory, and human-in-the-loop control?Recommendation	LangGraph / Deep Agents, cited 3 9 sources`bab619ea`	LangGraph / Deep Agents 0 sources`53e4b182`	LangGraph / Deep Agents 9 sources`3064d4a5`
06Which enterprise agent framework is strongest for .NET or Java teams that need plugins, governance, telemetry, and orchestration?Recommendation	None named 5 sources`41aa6e2b`	None named 0 sources`08ecea2f`	None named 9 sources`56d2c0fe`
07Recommend a cloud-native agent development framework with managed deployment, identity, security controls, and model flexibility.Recommendation	LangGraph / Deep Agents, cited 1 5 sources`57eaa9d0`	None named 0 sources`53fb8a40`	None named 7 sources`65dc78f4`
08Which agent framework is best for retrieval-heavy applications that use documents, data connectors, indexes, and citations?Recommendation	LlamaIndex 4 sources`3ee715c7`	LlamaIndex, cited 1 3 sources`a818595e`	LangGraph / Deep Agents, cited 1LlamaIndex 5 sources`04c14517`
09How should a team compare AI agent frameworks for abstraction overhead, model portability, lock-in, and debugging complexity?Commercial comparison	LangGraph / Deep Agents, cited 1 9 sources`9baa4355`	None named 0 sources`506d6fd4`	LangGraph / Deep Agents, cited 1LlamaIndex 6 sources`4d209a67`
10Which reliability criteria matter when choosing an agent framework, including state, retries, tracing, and deterministic tests?Commercial comparison	None named 8 sources`ad62cdcd`	None named 0 sources`d2bffe8a`	LangGraph / Deep Agents, cited 1 6 sources`2b425631`
11When should an engineering team adopt an agent framework instead of building a tool-calling loop directly on a model API?Commercial comparison	LangGraph / Deep Agents, cited 1 7 sources`06b2ca23`	None named 0 sources`dd1d48fe`	None named 6 sources`548af730`
12How should a company evaluate maintainer commitment, licensing, release stability, and migration risk in an agent framework?Commercial comparison	None named 4 sources`cf99c3b8`	None named 0 sources`1598be49`	None named 6 sources`7caf0102`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
langchain.com	10	3	2	1
youtube.com	7	7	3	1
reddit.com	7	7	2	2
pub.towardsai.net	6	5	2	1
github.com	6	4	2	1
langfuse.com	5	1	2	2
learn.microsoft.com	4	4	2	1
rank.ai	4	4	2	1
medium.com	4	4	2	2
mastra.ai	4	3	2	1
arxiv.org	3	3	2	1
braintrust.dev	3	3	2	2
arize.com	3	1	2	1
firecrawl.dev	3	1	2	1
monday.com	3	1	2	4
ai-sdk.dev	2	3	2	1
linkedin.com	2	3	2	5
cloud.google.com	2	2	2	1
dev.to	2	2	2	2
developersdigest.tech	2	2	2	2

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.ai-agent-frameworks-2026-07-27 / 4-ai-agent-frameworks-2026-07-27-models-64232fd32583

Primary brandQuestion typeModel APIQuestion contains

Run a question live

36.1%

of these answers name or cite LangGraph / Deep Agents

13 of 36 answers

72.2%

Its share of the compared brands' appearances

10

Answers citing its own site

12 links to its domains

3 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
LangGraph / Deep Agentslangchain.com	36.1%13 of 36	Primary	72.2%	22	10	12	3 of 3
LlamaIndexllamaindex.ai	11.1%4 of 36	-25.0 pts	22.2%	12	1	1	3 of 3
OpenAI Agents SDKopenai.com	2.8%1 of 36	-33.3 pts	5.6%	1	0	0	1 of 3
Claude Agent SDKanthropic.com	0.0%0 of 36	-36.1 pts	0.0%	0	0	0	0 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01What are the best open-source frameworks for building reliable AI agents in a production application?Recommendation	LangGraph / Deep Agents, cited 1 4 sources`f736fd64`	None named 0 sources`a6011974`	LangGraph / Deep Agents, cited 1OpenAI Agents SDK 6 sources`30488435`
02Recommend a Python-first agent framework with typed dependencies, structured outputs, tool validation, and testability.Recommendation	None named 6 sources`0a93806d`	LangGraph / Deep Agents 5 sources`c99bde45`	None named 5 sources`8ec5300a`
03Which TypeScript toolkit is best for streaming agent interfaces, tool calling, structured data, and multiple model providers?Recommendation	None named 8 sources`dda87429`	None named 0 sources`f09a530c`	None named 7 sources`aedcdcf7`
04Recommend a framework for role-based multi-agent teams, explicit handoffs, delegation, and human approval steps.Recommendation	None named 8 sources`6b63d488`	None named 0 sources`84227f68`	LangGraph / Deep Agents, cited 1 8 sources`23fecae1`
05What is the best framework for durable stateful agent graphs with checkpointing, retries, memory, and human-in-the-loop control?Recommendation	LangGraph / Deep Agents, cited 3 9 sources`bab619ea`	LangGraph / Deep Agents 0 sources`53e4b182`	LangGraph / Deep Agents 9 sources`3064d4a5`
06Which enterprise agent framework is strongest for .NET or Java teams that need plugins, governance, telemetry, and orchestration?Recommendation	None named 5 sources`41aa6e2b`	None named 0 sources`08ecea2f`	None named 9 sources`56d2c0fe`
07Recommend a cloud-native agent development framework with managed deployment, identity, security controls, and model flexibility.Recommendation	LangGraph / Deep Agents, cited 1 5 sources`57eaa9d0`	None named 0 sources`53fb8a40`	None named 7 sources`65dc78f4`
08Which agent framework is best for retrieval-heavy applications that use documents, data connectors, indexes, and citations?Recommendation	LlamaIndex 4 sources`3ee715c7`	LlamaIndex, cited 1 3 sources`a818595e`	LangGraph / Deep Agents, cited 1LlamaIndex 5 sources`04c14517`
09How should a team compare AI agent frameworks for abstraction overhead, model portability, lock-in, and debugging complexity?Commercial comparison	LangGraph / Deep Agents, cited 1 9 sources`9baa4355`	None named 0 sources`506d6fd4`	LangGraph / Deep Agents, cited 1LlamaIndex 6 sources`4d209a67`
10Which reliability criteria matter when choosing an agent framework, including state, retries, tracing, and deterministic tests?Commercial comparison	None named 8 sources`ad62cdcd`	None named 0 sources`d2bffe8a`	LangGraph / Deep Agents, cited 1 6 sources`2b425631`
11When should an engineering team adopt an agent framework instead of building a tool-calling loop directly on a model API?Commercial comparison	LangGraph / Deep Agents, cited 1 7 sources`06b2ca23`	None named 0 sources`dd1d48fe`	None named 6 sources`548af730`
12How should a company evaluate maintainer commitment, licensing, release stability, and migration risk in an agent framework?Commercial comparison	None named 4 sources`cf99c3b8`	None named 0 sources`1598be49`	None named 6 sources`7caf0102`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
langchain.com	10	3	2	1
youtube.com	7	7	3	1
reddit.com	7	7	2	2
pub.towardsai.net	6	5	2	1
github.com	6	4	2	1
langfuse.com	5	1	2	2
learn.microsoft.com	4	4	2	1
rank.ai	4	4	2	1
medium.com	4	4	2	2
mastra.ai	4	3	2	1
arxiv.org	3	3	2	1
braintrust.dev	3	3	2	2
arize.com	3	1	2	1
firecrawl.dev	3	1	2	1
monday.com	3	1	2	4
ai-sdk.dev	2	3	2	1
linkedin.com	2	3	2	5
cloud.google.com	2	2	2	1
dev.to	2	2	2	2
developersdigest.tech	2	2	2	2

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.ai-agent-frameworks-2026-07-27 / 4-ai-agent-frameworks-2026-07-27-models-64232fd32583

Ranks a reviewed Agent Frameworks brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.

4

Rank on this board

25 percent

Score

8

Answers behind the score

100% confidence · 1 of 1 components evidenced

What the score is built from

1 of 1 evidenced

Every component evidenced · 1 evidence record each

Components of Haystack's score
Component	Value	Contribution
OpenAI brand recommendation presence	25	25

Moved up since the previous snapshot

+2 places

Anthropic brand recommendation presence12.5 to 0
-12.5
OpenAI brand recommendation presence12.5 to 25
+12.5
OpenAI brand mention coverage8.333 to 16.667
+8.333
Anthropic brand mention coverage8.333 to 0
-8.333
Engine breadth3 to 2
-1
Mention share8 to 7.843
-0.157
Anthropic brand citation share0 to 0
0
Citation share0 to 0
0
Mention coverage11.111 to 11.111
0
Recommendation presence16.667 to 16.667
0
Gemini brand citation share0 to 0
0
Gemini brand mention coverage16.667 to 16.667
0
Gemini brand recommendation presence25 to 25
0
OpenAI brand citation share0 to 0
0

Where each number comes from

14 public records

Anthropic citation shareAnthropic brand citation share · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"ai-agent-frameworks-2026-07-27","runArtifactIds":["00935126-cf75-4970-b977-139c88a1a5c6","24522e51-8016-486f-b23f-d72b74bad970","982c3734-1f95-4160-a637-e03963be627b","e17daee9-963d-48a0-b5cb-f6bbdab448ad","3f9cd4b4-e3c5-477d-b268-f757997743bb","e5d9a9a6-5e82-4ed8-9479-30afd3bafa0f","9dceceba-1851-4a82-93da-42108895d880","7d48d3aa-1727-493a-a389-1f36f85e934f","e3725791-c297-45b1-b914-be373119a1ff","f198a76f-31ba-4973-b3e2-f020f688e429","057ec17c-7569-41b7-9ee3-7643bf282937","175a72eb-a027-4671-8f32-284c64fe7ba3","26b8e485-78ea-4b07-a5c5-b16dbfe83ba1","5b565155-69e7-42ad-ba77-79315acb0cb4","e1704759-5657-4ef3-a8f4-281e79dd9605","4f79351f-cf02-4dab-a278-f7befa532f80","38739c63-6914-4688-bfc2-37ae341c1165","2ee07ad9-ff9e-4726-b481-d02fb6dde7b1","59732202-e76a-4026-8f27-c904babcf11e","99e7248e-4a37-4a5d-a4a4-9309fc661ce8","d8ca45c8-82f4-4a72-9ca2-dc2796515884","7e683b37-ac45-414a-9e8b-33da4a465b50","045aa07c-0cd9-4a1f-b3ac-5ecbf2864b33","f2a4473b-7c6c-49b7-a092-1dc5474d0d11","0552e42d-7c0d-4619-8187-265d7c819ba4","fca4dc03-beaf-4529-891e-67d8516cd66d","dcb53fa1-77e7-44c6-884a-9f322601a592","4613ce01-b922-4c91-90c8-8ef25d1fb953","7f940397-f2cb-4aa5-85d7-23d0d5e9c663","5c9ef716-3432-4aad-9c25-93f9d440696d","e93789f6-73c1-4f43-b683-46d0e2772258","da91d6b2-fd20-4823-8a39-38cb32f680ac","726fbad1-9302-4ccc-80d8-9891aabac876","4d342f0b-7a6f-4c38-b511-32373edbb743","298fe4b4-73a7-4ce2-8dc1-50cfe331ac90","cf05659a-2fab-4d8b-865b-45f35ba1ea60"],"benchmarkVersion":"4-ai-agent-frameworks-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Anthropic mention coverageAnthropic brand mention coverage · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"ai-agent-frameworks-2026-07-27","runArtifactIds":["00935126-cf75-4970-b977-139c88a1a5c6","24522e51-8016-486f-b23f-d72b74bad970","982c3734-1f95-4160-a637-e03963be627b","e17daee9-963d-48a0-b5cb-f6bbdab448ad","3f9cd4b4-e3c5-477d-b268-f757997743bb","e5d9a9a6-5e82-4ed8-9479-30afd3bafa0f","9dceceba-1851-4a82-93da-42108895d880","7d48d3aa-1727-493a-a389-1f36f85e934f","e3725791-c297-45b1-b914-be373119a1ff","f198a76f-31ba-4973-b3e2-f020f688e429","057ec17c-7569-41b7-9ee3-7643bf282937","175a72eb-a027-4671-8f32-284c64fe7ba3","26b8e485-78ea-4b07-a5c5-b16dbfe83ba1","5b565155-69e7-42ad-ba77-79315acb0cb4","e1704759-5657-4ef3-a8f4-281e79dd9605","4f79351f-cf02-4dab-a278-f7befa532f80","38739c63-6914-4688-bfc2-37ae341c1165","2ee07ad9-ff9e-4726-b481-d02fb6dde7b1","59732202-e76a-4026-8f27-c904babcf11e","99e7248e-4a37-4a5d-a4a4-9309fc661ce8","d8ca45c8-82f4-4a72-9ca2-dc2796515884","7e683b37-ac45-414a-9e8b-33da4a465b50","045aa07c-0cd9-4a1f-b3ac-5ecbf2864b33","f2a4473b-7c6c-49b7-a092-1dc5474d0d11","0552e42d-7c0d-4619-8187-265d7c819ba4","fca4dc03-beaf-4529-891e-67d8516cd66d","dcb53fa1-77e7-44c6-884a-9f322601a592","4613ce01-b922-4c91-90c8-8ef25d1fb953","7f940397-f2cb-4aa5-85d7-23d0d5e9c663","5c9ef716-3432-4aad-9c25-93f9d440696d","e93789f6-73c1-4f43-b683-46d0e2772258","da91d6b2-fd20-4823-8a39-38cb32f680ac","726fbad1-9302-4ccc-80d8-9891aabac876","4d342f0b-7a6f-4c38-b511-32373edbb743","298fe4b4-73a7-4ce2-8dc1-50cfe331ac90","cf05659a-2fab-4d8b-865b-45f35ba1ea60"],"benchmarkVersion":"4-ai-agent-frameworks-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Citation shareCitation share · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Engine breadthEngine breadth · observed Sep 14, 2026, 12:00 AM UTC2 engines100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Mention coverageMention coverage · observed Sep 14, 2026, 12:00 AM UTC11.111 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Reviewed-brand presence shareMention share · observed Sep 14, 2026, 12:00 AM UTC7.843 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Recommendation-prompt presenceRecommendation presence · observed Sep 14, 2026, 12:00 AM UTC16.667 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini citation shareGemini brand citation share · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini mention coverageGemini brand mention coverage · observed Sep 14, 2026, 12:00 AM UTC16.667 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 14, 2026, 12:00 AM UTC25 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI citation shareOpenAI brand citation share · observed Sep 14, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI mention coverageOpenAI brand mention coverage · observed Sep 14, 2026, 12:00 AM UTC16.667 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 14, 2026, 12:00 AM UTC25 percent100% confidence
Source
Rank.ai Agent Frameworks Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source

Cite this data

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Plain textAgent Frameworks brands in OpenAI model API answers. Rank.ai, data as of September 14, 2026. https://www.rank.ai/rankings/agent-frameworks/ai-agent-frameworks-brand-openai-visibility
HTML<a href="https://www.rank.ai/rankings/agent-frameworks/ai-agent-frameworks-brand-openai-visibility">Agent Frameworks brands in OpenAI model API answers</a>, Rank.ai, data as of September 14, 2026
Markdown[Agent Frameworks brands in OpenAI model API answers](https://www.rank.ai/rankings/agent-frameworks/ai-agent-frameworks-brand-openai-visibility), Rank.ai, data as of September 14, 2026
APARank.ai. (2026). Agent Frameworks brands in OpenAI model API answers. Retrieved October 22, 2026, from https://www.rank.ai/rankings/agent-frameworks/ai-agent-frameworks-brand-openai-visibility

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<iframe src="https://www.rank.ai/embed/boards/ai-agent-frameworks-brand-openai-visibility" title="Agent Frameworks brands in OpenAI model API answers" width="100%" height="420" loading="lazy" style="border:1px solid #111;max-width:720px"></iframe>
<p style="font-size:12px">Source: <a href="https://www.rank.ai/rankings/agent-frameworks/ai-agent-frameworks-brand-openai-visibility">Agent Frameworks brands in OpenAI model API answers</a> by Rank.ai</p>

More in AI agent frameworks

Open source and vendor backed agent frameworks ranked across a fixed engineering buying corpus, with brand, prompt, engine and citation source views.

3 boards

AI agent framework rank

Reviewed agent frameworks ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

1LangGraph / Deep Agents37.5%
2CrewAI25%
3Mastra516.7%

AI agent framework presence

Reviewed frameworks ranked by the share of all the category's answers that name or cite them.

1LangGraph / Deep Agents36.1%
2CrewAI22.2%
3Mastra516.7%

AI agent framework citation share

Reviewed frameworks ranked by distinct answer-level citations to their canonical domains.

1LangGraph / Deep Agents36.4%
2Microsoft Agent Framework18.2%
3Vercel AI SDK318.2%

AI agent framework rank

Reviewed agent frameworks ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

AI agent framework presence

Reviewed frameworks ranked by the share of all the category's answers that name or cite them.

AI agent framework citation share

Reviewed frameworks ranked by distinct answer-level citations to their canonical domains.

See how often AI names you.

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
Who gets namedEvery competitor in the answers, most named first.
The pages AI readsThe sources behind each answer.
Three fixesWhat to fix first, with a brief for the first article.

Agent Frameworks brands in OpenAI model API answers

All 16 companies by OpenAI recommendation prompt presence

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

Haystack on Agent Frameworks Brands in OpenAI Model API Answers

What the score is built from

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Where each number comes from

More in AI agent frameworks

See how often AI names you.

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite