LlamaIndex (framework) vs OpenAI Agents SDK
LlamaIndex (framework) vs OpenAI Agents SDK: side-by-side comparison of two agent frameworks (no first-party memory layer) systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| LlamaIndex (framework) | OpenAI Agents SDK | |
|---|---|---|
| Capability band | competent | frontier |
| Capability composite | 70 | 78 |
| Cost tier | searched not found | searched not found |
| $/Mtok input | searched not found | searched not found |
| $/Mtok output | searched not found | searched not found |
| Use cases | Analytical Summarization, Memory Augmented Chat, Scoped Agentic, Multi Agent Coordination | Scoped Agentic, Multi Agent Coordination |
Where they differ (10)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| LlamaIndex (framework) | OpenAI Agents SDK | |
|---|---|---|
| Capability band | competent | frontier |
| Capability composite | 70 | 78 |
| Use cases | Analytical Summarization, Memory Augmented Chat, Scoped Agentic, Multi Agent Coordination | Scoped Agentic, Multi Agent Coordination |
| Type | Data framework for LLM apps | OpenAI's official agent framework |
| Created | 2022 | 2025 |
| Latest release | v0.14.25 (2026-09-21) | v0.24.0 (2026-10-15) — Python; JS/TS @openai/agents v0.21.0 (2026-10-20) |
| GitHub | run-llama/llama_index — ~53k stars, last commit 2026-10 | openai/openai-agents-python — ~30k stars, last commit 2026-10 (JS: openai/openai-agents-js ~3.9k) |
| Funding | $27M total raised through Series A 2024-06 ($19M, Norwest led; $200M valuation rumored). | searched not found |
| Deployment | Both (self-hosted + managed cloud) — OSS library; LlamaAgents workflows deploy to LlamaCloud or self-host | Self-hosted only — library |
| MCP | yes — use MCP server tools in workflows and serve LlamaIndex workflows as MCP servers | yes — HostedMCPTool plus MCPServerStreamableHttp, MCPServerStdio and MCPServerSse (deprecated) server classes |
At a glance
| LlamaIndex (framework) | OpenAI Agents SDK | |
|---|---|---|
| Section | Agent frameworks (no first-party memory layer) | Agent frameworks (no first-party memory layer) |
| Tier | T1 | T1 |
| Type | Data framework for LLM apps | OpenAI's official agent framework |
| Created | 2022 | 2025 |
| Latest release | v0.14.25 (2026-09-21) | v0.24.0 (2026-10-15) — Python; JS/TS @openai/agents v0.21.0 (2026-10-20) |
| License | MIT | MIT |
| GitHub | run-llama/llama_index — ~53k stars, last commit 2026-10 | openai/openai-agents-python — ~30k stars, last commit 2026-10 (JS: openai/openai-agents-js ~3.9k) |
| Pricing | searched not found | searched not found |
| Funding | $27M total raised through Series A 2024-06 ($19M, Norwest led; $200M valuation rumored). | searched not found |
| Deployment | Both (self-hosted + managed cloud) — OSS library; LlamaAgents workflows deploy to LlamaCloud or self-host | Self-hosted only — library |
| API surface | searched not found | searched not found |
| Multi-tenancy | searched not found | searched not found |
| MCP | yes — use MCP server tools in workflows and serve LlamaIndex workflows as MCP servers | yes — HostedMCPTool plus MCPServerStreamableHttp, MCPServerStdio and MCPServerSse (deprecated) server classes |
| A2A | searched not found | searched not found |
| OpenTelemetry | searched not found | searched not found |
| Optimised for | searched not found | searched not found |
| Anti-fit | searched not found | searched not found |
Pros & cons
LlamaIndex (framework)
Pros: searched not found
Cons: searched not found
OpenAI Agents SDK
Pros: searched not found
Cons: searched not found