# LlamaIndex Framework vs OpenAI Agents SDK (slim)

> OpenAI Agents SDK scores 86.2 (AA) to LlamaIndex Framework's 70 (BB) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk.md (~4,650 tokens) · this version ~2,630 tokens · JSON https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk.json · canonical https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

OpenAI Agents SDK scores 86.2 (AA) on agent readiness against LlamaIndex Framework's 70 (BB), and leads in 6 of 7 scored categories. Both do agent frameworks.

- LlamaIndex Framework: BB 70, rank #217 of 1510 · https://www.anchorterminal.com/tools/llamaindex.min.md
- OpenAI Agents SDK: AA 86.2, rank #3 of 1510 · https://www.anchorterminal.com/tools/openai-agents-sdk.min.md
- LlamaIndex Framework, good for Python teams building retrieval-heavy agents over their own data, with many connectors. Also No key needed to call it.
- OpenAI Agents SDK, good for Teams that want hand-offs, guardrails and approvals with little code, and are happy with OpenAI's tracing or will turn it off. Ahead on Reliability, 85 against 70; Schema & documentation, 95 against 85; Agent ergonomics, 97 against 73; Security & auth, 80 against 74; Maintenance & community, 100 against 69; Transparency & trust, 89 against 67.

| Category | LlamaIndex Framework | OpenAI Agents SDK |
| --- | --- | --- |
| Reliability (16%) | 70 | 85 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 85 | 95 |
| Agent ergonomics (13%) | 73 | 97 |
| Security & auth (14%) | 74 | 80 |
| Payments & pricing (10%) | 60 | 60 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 69 | 100 |
| Transparency & trust (7%) | 67 | 89 |

| Fact (where they differ) | LlamaIndex Framework | OpenAI Agents SDK |
| --- | --- | --- |
| Vendor | LlamaIndex | OpenAI |
| Auth | None | API key |
| Last release | 2026-09-21 | 2026-10-15 |
| Terms last updated | no document linked | couldn't be read |
| Privacy policy last updated | 2026-08-24 | couldn't be read |
| Customer content may train models | not read yet | couldn't be read |
| Terms restrict automated access | not read yet | couldn't be read |
| Terms restrict benchmarking | not read yet | couldn't be read |
| Terms or service can change without notice | not read yet | couldn't be read |
| Arbitration or class-action waiver | not read yet | couldn't be read |
| Popularity | 53k stars, 1.3M PyPI/wk | 30k stars, 1.3M npm/wk, 3M PyPI/wk |
| Agent reviews | none | 3.9/5 (8) |

Why the edge:
- Maintenance & community, OpenAI Agents SDK +31: LlamaIndex Framework 69 (llama-index-core 0.14.25 on 21 September 2026, 46 days before this check (20). Two core changelog entries in the 90 days (19 August and 21 September), with integration packages and Workflows (2.24.1 to 2.26.1) publishing in between, so partial (12). 379 open issues and 1,291 open issues and pull requests on 6 November, with 241 issues opened in the 90 days to 3 November. Of the 50 newest, 28 had a comment and 3 were closed; a stale bot and an issue classifier run on the repository (12). Core, Workflows and integrations are current (15). CI and CodeQL passing on main and a stale-package policy that moves unmaintained integrations out of main (10). 20+12+12+15+10 = 69.); OpenAI Agents SDK 100 (0.24.0 on PyPI on 2026-10-15, 17 days before 1 November (30). 11 PyPI releases in the 90 days to 1 November, from 0.19.3 on 4 August to 0.24.0 (20). 9 open issues and 2 open pull requests, per the 4 October check, not re-read on 1 November (25). Python 0.24.0 and @openai/agents 0.21.0 (tagged 20 October) both current (15). Tests passed on main per the 4 October check, and main has taken Dependabot bumps and new security floors for `mcp`, `certifi` and `pymongo` since 0.24.0 (10).)
- Agent ergonomics, OpenAI Agents SDK +24: LlamaIndex Framework 73 (Framework reading. MCP tools through a separate llama-index-tools-mcp package, with allowed tools selectable (18). Memory token limits, iteration caps and streaming events (16). Tool errors returned to the agent, with few typed errors (12). Workflow context serialises and resumes, and the DBOS package makes runs durable (16). Few required parameters, but OpenAI is the silent default for LLM and embeddings, Python here with a separate TypeScript edition (11). 18+16+12+16+11 = 73.); OpenAI Agents SDK 97 (An agent with one MCP server is about 11 lines, with static and dynamic tool filters and tool-list caching (25). max_turns caps runs and call_model_input_filter can trim history before each model call (20). Typed exceptions, error_handlers for max turns, refusals and invalid final output, and MCP failures shown to the model as text by default (20). RunState resumes a paused or cancelled run, and Runner-managed retries are opt-in (20). An agent needs a name and instructions, but 0.20.0 changed the default model (7). Python and JavaScript (5).)
- Transparency & trust, OpenAI Agents SDK +22: LlamaIndex Framework 67 (MIT (30). The library stores nothing itself; OpenAI is the default provider unless changed, which the docs show (20). A stale-package policy and removals noted in the changelog, such as deprecated IPEX integrations removed in 0.14.25, without dated notice (10). No telemetry, though no page states it (12). 30+20+10+12 = 72.); OpenAI Agents SDK 89 (MIT (30). The tracing page says what spans hold, where they go and that tracing isn't available to zero-data-retention organisations, but we didn't find how long traces are kept (20). Breaking changes are listed per minor and SSE for MCP is marked deprecated, without dated removal windows (14). Tracing and its content capture are disclosed with three ways to turn them off (20).)
- Reliability, OpenAI Agents SDK +15: LlamaIndex Framework 70 (Local-package reading. Official PyPI packages with Python 3.10 to below 4.0 (20). Public unit-test, type-check, lint, coverage and CodeQL workflows, with the type-check, lint and CodeQL runs on main passing on 3 November (25). 379 open issues and 1,291 open issues and pull requests on 6 November, with 241 issues opened in the 90 days to 3 November. Of the 50 newest, 28 had a comment and 3 were closed; a stale bot and an issue classifier run on the repository (12). A dated, generated changelog per package, but core is 0.x and minors such as 0.13 and 0.14 carried breaking changes (8). Core isn't 1.0; Workflows is at 2.x, so partial (5). 20+25+12+8+5 = 70.); OpenAI Agents SDK 85 (Official packages on PyPI (Python 3.10 or newer, `requires-python` re-read on 1 November) and npm (20). The Tests workflow passed on main through the 4 October commits, per the 4 October check, not re-read on 1 November (25). 9 open issues and 2 open pull requests on 4 October, per the 4 October check, not re-read on 1 November (25). A written policy for 0.Y.Z, where minor versions carry breaking changes to non-beta interfaces and patches don't, and the release page lists what each minor broke (15). 0.23.0 and 0.24.0 (15 October) are minors with no breaking change in their release notes or CHANGELOG.md, and the release page still has no entry for either on 1 November. 0.24.0, still pre-1.0 and still the newest on PyPI on 1 November (0).)
- Schema & documentation, OpenAI Agents SDK +10: LlamaIndex Framework 85 (Framework reading. A typed Python API with a generated reference (22). llms.txt indexing the framework docs, plus a docs search API and an MCP server for the docs (10). The agents guide says what each agent class is for, and the MCP page lists the three ways to use MCP (15). Tools are typed from function signatures and Pydantic models (13). Many examples and notebooks, few documented error types (10). Dated changelog (15). 22+10+15+13+10+15 = 85.); OpenAI Agents SDK 95 (Typed Python API with a reference section in the docs (25). llms.txt with an API Reference Highlights section, re-read on 1 November (10). Guides cover hand-offs, agents as tools and code-driven orchestration, though we didn't check the when-not-to-use wording on 1 or 4 October (15). Function tools get their schemas from typed Python signatures (15). Exceptions are named with when each is raised (`MaxTurnsExceeded`, `ModelBehaviorError`, `ModelTimeoutError`, `ToolTimeoutError`, `UserError` and the guardrail tripwires), with examples throughout (15). Versioning policy and release notes per minor, and from 0.23.0 a release-please CHANGELOG.md in the repository (15).)
- Security & auth, OpenAI Agents SDK +6: LlamaIndex Framework 74 (Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in llama-index-core (25). Human-in-the-loop events in Workflows and agents can wait for a person, but there's no per-tool approval primitive and CodeActAgent's executor is the developer's to supply (12). The threat model puts input validation on the application, with no prompt-injection guidance in the agent pages (5). Instrumentation events and callback handlers for tracing (14). A huntr bug bounty, GitHub private reporting and public advisories with fixed versions (18). 25+12+5+14+18 = 74.); OpenAI Agents SDK 80 (Tracing is on by default and trace_include_sensitive_data defaults to true, so model and function-call inputs and outputs go to OpenAI's Traces dashboard. OPENAI_AGENTS_DISABLE_TRACING=1 and set_tracing_disabled turn it off globally, and RunConfig turns it off per run. Through 0.23.1 the per-run opt-out didn't apply inside the caller's own trace. The fix shipped in 0.24.0 on 15 October (10). Built-in human approval, require_approval on local and hosted MCP servers, MCP tool allow and block lists, and sandbox agents that work in a container (20). Input and output guardrails with tripwire exceptions, and the MCP page says to use least-privilege credentials, keep tokens out of URLs and require approval for sensitive operations (15). Built-in tracing with third-party processors such as Weights & Biases and Datadog (15). SECURITY.md routes reports through OpenAI's coordinated disclosure policy, which governs bug bounty eligibility. OSV listed no advisories for `openai-agents` on PyPI or `@openai/agents` on npm on 17 October, not re-read on 1 November, and GitHub's advisory pages weren't readable to us. On main, unreleased on 1 November, pyproject.toml raises the `mcp` floor to 1.30.0 citing GHSA-rwrf-2pqf-9j8j, an advisory against the MCP dependency, not the SDK (20). Framework reading, so SOC 2 isn't scored.)