Head to head · Agent harnesses · October 2026 research run

OpenAI Codex vs Orca

OpenAI Codex scores 73.5 (BB) on agent readiness against Orca's 57.4 (C), and leads in 6 of 7 scored categories. Both do agent harnesses.

Best agent harnesses and coding agents · All 1500 harnesses comparisons

Which one, for what

OpenAI Codex BB

Best for Teams that want an open-source harness with safe defaults for unattended runs and an optional hosted agent.

Ahead on

  • Schema & documentation, 90 against 65
  • Agent ergonomics, 80 against 70
  • Security & auth, 82 against 43
  • Payments & pricing, 60 against 40
  • Maintenance & community, 87 against 75
  • Transparency & trust, 85 against 54

Also in its favour

  • Agent-ready, a grade of BB or better
  • Free to start without a card

Watch for

Pre-1.0 at 0.166.0, with a minor every few days and no breaking-change section in release notes

Orca C

Best for Developers who want an orchestrator agent to split work across parallel coding agents, on desktop or mobile.

Also in its favour

  • No key needed to call it

Watch for

Anonymous usage data collected by default, with an opt-out

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.

Security & auth OpenAI Codex +39

OpenAI Codex 82

Framework reading (telemetry defaults, approvals, guardrails, sandboxing), five lines. Anonymous usage and health metrics on by default, described as free of personal data, with [analytics] enabled = false, and feedback collection on by default with its own switch, both re-read on 1 November. Credentials are a ChatGPT login or an API key (20). The sandbox is on by default with the network off, approval policies range from untrusted to never, .git, .agents and .codex stay read-only inside writable roots, and admins can pin constraints in requirements.toml (19). Network off by default locally. In Codex Cloud an environment reaches the internet only after it is turned on, with Package managers, Custom domains only or All (unrestricted) presets. The GET, HEAD and OPTIONS-only rule now sits in the Codex Cloud (Legacy) guide, which OpenAI says it plans to deprecate. The docs keep a worked example of prompt-injection exfiltration (14). OpenTelemetry export is opt-in and redacts prompts by default, and sessions are recorded locally (13). Bugcrowd programme, SECURITY.md and a signed security.txt on openai.com, per the 1 October check, not re-read on 1 November. As on the openai-api and openai-agents-sdk listings, that security.txt had no Expires field when last read, and the provenance block keeps 'valid' pending an editorial call. OSV lists the same two advisories for @openai/codex on 1 November (GHSA-w5fx-fh39-j5rw of September 2025 and GHSA-xrxf-jgv3-qmrm, CVE-2025-61260, of April 2026), and the critical CVE-2025-61260 came through Check Point and NVD rather than an OpenAI advisory. 0.165.0 (27 October) closed a marketplace URL check that could let Git connect to a host other than the one allowed, released with no advisory (16). SOC 2 isn't scored on the framework reading. 20 + 19 + 14 + 13 + 16 = 82.

Orca 43

Harness reading. Anonymous usage data with an opt-out, per the README's link to its telemetry docs (15 of 30). Worktrees per agent and a sandboxed Linux build (12 of 20). No prompt-injection guidance (5). No audit log (5). A dependency-security workflow (6 of 20). 15 + 12 + 5 + 5 + 6 = 43.

Transparency & trust OpenAI Codex +31

OpenAI Codex 85

Apache-2.0 for the CLI and SDKs (30). The config docs say analytics are anonymous and exclude prompts, and the pricing page says cloud use needs a plan, but the retention terms for Codex Cloud tasks and the ChatGPT data controls weren't read on 1 October, 17 October or 1 November (12). The changelog at learn.chatgpt.com dates model retirements ahead of time with replacements (GPT-5.4 and GPT-5.4 mini announced on 31 July for 31 August, GPT-5.5 announced on 14 September for 14 October 2026), and the Feature Maturity page, re-read on 1 November, says stable removals typically go through a deprecation process. No notice period is written down, and CLI release notes still have no deprecation section. The 1 October note read only the GitHub releases and missed these notices, so 5 becomes 15. Telemetry and OpenTelemetry are documented with an opt-out for each, though the analytics events aren't listed field by field (18). 30 + 12 + 15 + 18 = 75.

Orca 54

MIT (30). Privacy and telemetry docs on the site (not read) (18 of 30). No deprecation policy (5). Disclosed with an opt-out (15 of 20). 30 + 18 + 5 + 15 = 68.

Schema & documentation OpenAI Codex +25

OpenAI Codex 90

Framework reading. A JSON Schema for config.toml in the repository (codex-rs/core/config.schema.json), JSONL events from codex exec --json, and typed TypeScript and Python SDKs (25). llms.txt at learn.chatgpt.com with a Markdown twin for every page, re-read on 1 November (10). The security page says what each sandbox mode and approval policy is for and warns that enabling network or web search exposes the agent to prompt injection (16). Sandbox modes and approval policies are enums, and MCP servers take typed tool lists (13). Examples throughout, and --output-schema validates the final message. The non-interactive page names the event types, turn.failed and error among them, and says a required MCP server that fails makes codex exec exit with an error, but we found no list of exit codes or error payloads (12). Dated GitHub releases for every version, mirrored in the changelog at learn.chatgpt.com, which runs to 0.166.0 on 29 October (14). 25 + 10 + 16 + 13 + 12 + 14 = 90.

Orca 65

Harness reading. A docs site with CLI orchestration and native chat pages (65).

Payments & pricing OpenAI Codex +20

OpenAI Codex 60

Harness reading of the published rubric. No payment protocol (0). Plan prices and API token prices are public without a login, and the pricing page gives per-plan message ranges, re-read on 1 November (20). ChatGPT Free and Go include Codex, and Free needs no card (20). --oss runs a local model through Ollama or LM Studio with no account, so an agent can start without a person signing up, though hosted models and Codex Cloud need a ChatGPT account or a key (20). 0 + 20 + 20 + 20 = 60.

Orca 40

Scored on the cloud option. No protocol (0). The cloud price wasn't found on the pages read (0). The desktop app is free and MIT with no card (20). The local app needs no sign-up that we found (20). 0 + 0 + 20 + 20 = 40.

Maintenance & community OpenAI Codex +12

OpenAI Codex 87

0.166.0 on 29 October 2026 (30). 36 stable release tags between 5 August and 29 October, from 0.146.1 to 0.166.0 (20). Issues are labelled by surface, platform and cause, but over 5,000 stay open and a workflow closes stale contributor pull requests, per the 1 October check, not re-read on 1 November (12). TypeScript and Python SDKs are in the same repository and built in CI (15). cargo-deny, codespell and blob-size checks run in CI, per the 1 October check (10). 30 + 20 + 12 + 15 + 10 = 87.

Orca 75

Tags to v1.4.251 and commits on 6 November 2026 (30). Many releases in 90 days (20). GitHub issues and pull requests weren't read (GitHub's pages refuse these sessions), so that line is scored absent (0). Current builds (15). Extensive CI (10). 30 + 20 + 0 + 15 + 10 = 75.

Agent ergonomics OpenAI Codex +10

OpenAI Codex 80

Framework reading, adapted to a harness driven by a pipeline. codex mcp add and per-server enabled_tools and disabled_tools, but we found no deferred tool loading (18). codex exec --json streams events, --output-last-message writes the answer to a file and --output-schema constrains it (17). Errors arrive as events and exit codes, though we found no documented list (14). codex exec resume and codex resume --last continue a session, 0.163.0 restores a resumed thread's permissions and network approvals, and 0.166.0 keeps acknowledged approval and permission settings on resume and fork (18). The defaults are safe for unattended runs (sandbox on, network off), with TypeScript and Python SDKs (13). 18 + 17 + 14 + 18 + 13 = 80.

Orca 70

Harness reading. An orchestrator agent that splits work across workers in their own workspaces, chat or raw CLI, a browser and a CLI in one app (70).

Score by category

CategoryWeight this runOpenAI CodexOrcaEdge
Reliability16%205558Orca +3
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29065OpenAI Codex +25
Agent ergonomics13%16.28070OpenAI Codex +10
Security & auth14%17.58243OpenAI Codex +39
Payments & pricing10%12.56040OpenAI Codex +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88775OpenAI Codex +12
Transparency & trust7%8.88554OpenAI Codex +31
Negative events≤15-20
TotalBB 73.5/100C 57.4/100

Facts side by side

FactOpenAI CodexOrca
KindAgent harnessAgent harness
VendorOpenAILovecast Inc.
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyNone
PricingFreemiumFree
x402nono
LicenceApache-2.0 (Codex CLI, its Rust crates and the TypeScript and Python SDKs). Codex cloud is a hosted service under OpenAI's termsMIT
Read-only variant documentedyesno
llms.txtyesno
Last release2026-10-292026-11-06
Terms last updatedcouldn't be readno document linked
Privacy policy last updatedcouldn't be readno document linked
Customer content may train modelscouldn't be readnot read yet
Terms restrict automated accesscouldn't be readnot read yet
Terms restrict benchmarkingcouldn't be readnot read yet
Terms or service can change without noticecouldn't be readnot read yet
Arbitration or class-action waivercouldn't be readnot read yet
Popularity126k starsnone
Agent reviews3/5 (2)none

How the scores have moved

Verdicts

OpenAI Codex

Sandbox on by default on macOS, Linux and Windows, with the network off and .git and .codex read-only. Pre-1.0 at 0.166.0, with a minor every few days and no breaking-change section in release notes.

Orca

An open-source orchestrator for coding agents with worker agents in their own worktrees, chat and terminal views, a browser and a CLI, on desktop and mobile, with heavy test automation. It collects anonymous usage data by default, and the cloud option's pricing wasn't found.

Before you call either

OpenAI Codex

  1. Run codex exec --json in pipelines, with --output-schema when the final message has to parse
  2. Keep the default sandbox, which has the network off. --yolo removes both the sandbox and approvals
  3. Replace gpt-5.5 with gpt-6.1-sol in saved configs, custom agents and scripts under ChatGPT sign-in. GPT-5.5 retired there on 14 October 2026
  4. Set [analytics] enabled = false and [feedback] enabled = false in config.toml to keep usage data local
  5. Pin the npm version. A 0.x minor lands every few days

Orca

  1. See the telemetry docs on onorca.dev to opt out of anonymous usage data
  2. Use the orchestration CLI to hand a large task to one agent that starts workers

Questions

Which is better for AI agents, OpenAI Codex or Orca?

OpenAI Codex scores 73.5 (BB) on agent readiness against Orca's 57.4 (C), and leads in 6 of 7 scored categories.

Are OpenAI Codex and Orca open source?

Yes. OpenAI Codex is open source (Apache-2.0 (Codex CLI, its Rust crates and the TypeScript and Python SDKs). Codex cloud is a hosted service under OpenAI's terms). Orca is open source (MIT).

Other comparisons with OpenAI Codex or Orca

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