Head to head · Agent frameworks · October 2026 research run

LlamaIndex Framework vs smolagents

LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories. Both do agent frameworks.

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Which one, for what

LlamaIndex Framework BB

Best for Python teams building retrieval-heavy agents over their own data, with many connectors.

Ahead on

  • Reliability, 70 against 64
  • Agent ergonomics, 73 against 68
  • Security & auth, 74 against 66
  • Maintenance & community, 69 against 34

Also in its favour

  • Agent-ready, a grade of BB or better

Watch for

Core is 0.14.x, and minor versions such as 0.13 and 0.14 carried breaking changes

smolagents C

Best for Small Python projects and research that want code-writing agents with minimal abstraction.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

No release since 1.26.0 on 29 May 2026, and few commits to main since August

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Maintenance & community LlamaIndex Framework +35

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.

smolagents 34

v1.26.0 on 29 May 2026, 161 days before this check (10). No release in the 90 days to 6 November (0). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Python only, and the package is the current one (10). CI with actions pinned to commit SHAs and Dependabot for actions (8). 10+0+6+10+8 = 34.

Security & auth LlamaIndex Framework +8

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.

smolagents 66

Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in the source (25). No human approval hook beyond step callbacks; the local executor restricts imports but the guide says it isn't a security tool, and isolation needs a remote executor (10). The secure execution guide covers LLM-generated code risks, without prompt-injection guidance for tool output (7). OpenTelemetry tracing through OpenInference and run inspection (12). SECURITY.md with private reporting and CVE credit, and the remote-executor RCE was fixed in public, but two 2026 CVE records say the vendor didn't respond (12). 25+10+7+12+12 = 66.

Reliability LlamaIndex Framework +6

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.

smolagents 64

Local-package reading. Official PyPI package with Python 3.10 or newer (20). A public tests workflow runs pytest on Python 3.10 and 3.12 for pushes and pull requests; whether main passes wasn't read (15). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Release notes on GitHub tags but no changelog file, and the remote WasmExecutor was removed in a minor release (8). 1.0 since 31 December 2024 (15). 20+15+6+8+15 = 64.

Agent ergonomics LlamaIndex Framework +5

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.

smolagents 68

Framework reading. MCPClient loads an MCP server's tools in a few lines (20). max_steps, planning intervals and final_answer_checks bound a run (16). Errors from tools and code go back to the model as observations (14). No built-in retry, idempotency or resume beyond replaying memory (8). Few required parameters and many providers, Python only, and the default model needs a Hugging Face token (10). 20+16+14+8+10 = 68.

Score by category

CategoryWeight this runLlamaIndex FrameworksmolagentsEdge
Reliability16%207064LlamaIndex Framework +6
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28581LlamaIndex Framework +4
Agent ergonomics13%16.27368LlamaIndex Framework +5
Security & auth14%17.57466LlamaIndex Framework +8
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86934LlamaIndex Framework +35
Transparency & trust7%8.86765LlamaIndex Framework +2
Negative events≤15-2-6
TotalBB 70/100C 58.7/100

Facts side by side

FactLlamaIndex Frameworksmolagents
KindAgent frameworkAgent framework
VendorLlamaIndexHugging Face
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceMITApache-2.0
Read-only variant documentednono
llms.txtyesyes
Last release2026-09-212026-05-29
Terms last updatedno document linked2022-09-15
Privacy policy last updated2026-08-242023-03-28
Customer content may train modelsnot read yetnot found in the text
Terms restrict automated accessnot read yetnot found in the text
Terms restrict benchmarkingnot read yetnot found in the text
Terms or service can change without noticenot read yetyes
Arbitration or class-action waivernot read yetnot found in the text
Popularity53k stars, 1.3M PyPI/wk30k stars, 171k PyPI/wk

Verdicts

LlamaIndex Framework

An MIT Python framework for retrieval and agents, with three agent types, multi-agent AgentWorkflow, resumable event-driven Workflows, MCP tools and a huntr bug bounty, and no telemetry found. Core is still 0.14 with breaking minors, OpenAI is the silent default, and approval and injection handling are left to the application.

smolagents

A compact Python library for code-writing and tool-calling agents, with MCP tools, any model provider and remote sandboxes through E2B, Docker, Modal or Blaxel. The newest release is 1.26.0 of 29 May 2026, a critical remote-executor RCE took about eight weeks to fix, and the local executor isn't a security boundary.

Before you call either

LlamaIndex Framework

  1. Set Settings.llm and Settings.embed_model explicitly so calls don't go to OpenAI by default
  2. Install llama-index-tools-mcp for MCP tools and pass only the allowed tools the task needs
  3. Use Workflow human-in-the-loop events before tools that write or send
  4. Pin llama-index-core to a minor version, since minors have broken APIs
  5. Upgrade llama-index-core to 0.13.0 or later to clear the 2025 advisories

smolagents

  1. Run CodeAgent with executor_type set to e2b, docker, modal or blaxel whenever the model or its inputs aren't trusted
  2. Use smolagents 1.24.0 or later to get the remote-executor deserialisation fix
  3. Set max_steps and final_answer_checks so a run stops on its own
  4. Pass structured_output explicitly to MCPClient to avoid the default-change warning
  5. Pin the version, since minor releases have removed APIs

Questions

Which is better for AI agents, LlamaIndex Framework or smolagents?

LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories.

Are LlamaIndex Framework and smolagents open source?

Yes. LlamaIndex Framework is open source (MIT). smolagents is open source (Apache-2.0).

Other comparisons with LlamaIndex Framework or smolagents

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