Head to head · Agent harnesses · October 2026 research run

OpenAI Codex vs Verdent

OpenAI Codex scores 73.5 (BB) on agent readiness against Verdent's 39.7 (E), and leads in every scored category. 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

  • Reliability, 55 against 43
  • Schema & documentation, 90 against 55
  • Agent ergonomics, 80 against 35
  • Security & auth, 82 against 33
  • Payments & pricing, 60 against 20
  • Maintenance & community, 87 against 61
  • Transparency & trust, 85 against 55

Also in its favour

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

Watch for

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

Verdent E

Best for A person who wants a desktop app to plan and run several coding tasks at once, possibly on their own Claude Code or Codex.

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

Watch for

No CLI, print mode, API or SDK, so a pipeline can't start or read a run except through a paired chat bot

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 +49

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.

Verdent 33

Framework reading (telemetry defaults, approvals, guardrails, sandboxing). Conversation history and tool results go to Verdent's US servers and on to Azure, Bedrock or Vertex, with zero data retention stated for Vertex and Bedrock only. Event logging to log.verdent.ai has no documented opt-out. BYOA keys stay on the machine (10). Plan Mode is read-only, Agent Mode asks before destructive commands and edits outside scope, and workers are isolated by git worktree, but there is no sandbox or network control and the approval list isn't enumerated (9). No prompt-injection guidance found, while web search and fetch results enter the context (2). Usage history in the dashboard, no audit log found (5). A security page with a disclosure address and a five-day acknowledgement, SOC 2 and ISO/IEC 42001 being pursued rather than held, no security.txt and no bug bounty (7). 10+9+2+5+7 = 33.

Agent ergonomics OpenAI Codex +45

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.

Verdent 35

Harness reading. MCP servers per project or globally, subagents, skills and rules, but no per-tool disabling or deferred loading found (10). No output-size, turn-limit or budget controls for a run were found beyond credit balances (5). No exit codes or error format, since there is no headless mode (3). Parallel workers in git worktrees and a review column make runs reviewable and reversible, with no resume by ID documented (10). No CLI, API or SDK. A pipeline can only reach Manager through a paired Telegram, Slack or Feishu bot (7). 10+5+3+10+7 = 35.

Payments & pricing OpenAI Codex +40

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.

Verdent 20

Harness reading of the published rubric, scored on the Verdent subscription the agent needs. No payment protocol (0). Plan prices from $5 a month, top-up prices and the credit value of about $0.059 are public without a login (20). Free Mode and the free trial ended on 29 October 2026, so there is no free tier (0). A person signs up in a browser (0). 0+20+0+0 = 20.

Schema & documentation OpenAI Codex +35

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.

Verdent 55

Framework reading for a harness. No schema for settings or output, only mcp.json examples in the standard mcpServers shape (5). Every current docs page has a Markdown twin at the same path with .md, though no llms.txt (10). The docs say when to use Agent Mode or Plan Mode and what Plan Mode can't do, but the Agent Mode page lists the actions that need approval only as "certain tool executions" and "destructive operations" (12). Modes and BYOA agent types are enumerated, permissions are not (5). Examples on the MCP, BYOA and messaging pages, and a recovery page, with no error codes (8). Version numbers and a dated public changelog (15). The archived 1.0 docs are still served beside the current ones. 5+10+12+5+8+15 = 55.

Transparency & trust OpenAI Codex +30

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.

Verdent 55

Proprietary, under terms from Verdent AI, Inc. that are clear on use and ownership (15). The privacy policy and security page agree that data stays in the US and that input isn't trained on without consent, and the security page lists subprocessors. The privacy policy gives no retention periods, names MiniMax as a provider the security list leaves out, and deletion is by email request (14). The credit bonus carries a promise of 15 days' notice, but Free Mode was retired on the day v2.18.0 shipped and no deprecation policy was found (6). Subprocessors and their locations are listed, and the domains the app calls are named, with event logging undescribed (12). 15+14+6+12 = 47.

Maintenance & community OpenAI Codex +26

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.

Verdent 61

Closed service. v2.18.0 on 29 October 2026, eight days before this check (30). More than three dated releases in the 90 days from 8 August, among them 2.10.0 to 2.18.0 (20). A dated public changelog, a support address, Discord and a subreddit, with no public tracker to read reply times (8). No official SDK or MCP server to keep current (0). No public packages or CI to judge (3). 30+20+8+0+3 = 61.

Score by category

CategoryWeight this runOpenAI CodexVerdentEdge
Reliability16%205543OpenAI Codex +12
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29055OpenAI Codex +35
Agent ergonomics13%16.28035OpenAI Codex +45
Security & auth14%17.58233OpenAI Codex +49
Payments & pricing10%12.56020OpenAI Codex +40
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88761OpenAI Codex +26
Transparency & trust7%8.88555OpenAI Codex +30
Negative events≤15-2-2
TotalBB 73.5/100E 39.7/100

Facts side by side

FactOpenAI CodexVerdent
KindAgent harnessAgent harness
VendorOpenAIVerdent AI, Inc.
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyOAuth or key
PricingFreemiumPaid
x402nono
LicenceApache-2.0 (Codex CLI, its Rust crates and the TypeScript and Python SDKs). Codex cloud is a hosted service under OpenAI's termsProprietary. The terms of use from Verdent AI, Inc. forbid reverse engineering or copying any component, and no source is published
Read-only variant documentedyesyes
llms.txtyesno
Last release2026-10-292026-10-29
Terms last updatedcouldn't be read2026-05-25
Privacy policy last updatedcouldn't be read2026-05-26
Customer content may train modelscouldn't be readyes
Terms restrict automated accesscouldn't be readyes
Terms restrict benchmarkingcouldn't be readnot found in the text
Terms or service can change without noticecouldn't be readyes
Arbitration or class-action waivercouldn't be readnot found in the text
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.

Verdent

A desktop and editor coding agent that splits a goal into parallel workers in git worktrees, with a read-only Plan Mode, MCP servers and the option to run workers on Claude Code or Codex. It has no CLI, API or sandbox, sends context through Verdent's servers, and has had no free tier since 29 October 2026.

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

Verdent

  1. Don't plan to drive Verdent headless. Hand the task to the person using the desktop app, or use a harness with a print mode
  2. Start large changes in Plan Mode and review plan.md before switching to Agent Mode
  3. Add MCP servers in the project's .mcp.json or ~/.verdent/mcp.json in the mcpServers shape
  4. Keep work under git, since rollback relies on git and there is no sandbox
  5. Budget in credits at about $0.059 each, because there is no free allowance since 29 October 2026

Questions

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

OpenAI Codex scores 73.5 (BB) on agent readiness against Verdent's 39.7 (E), and leads in every scored category.

Are OpenAI Codex and Verdent open source?

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). No open-source release is listed for Verdent.

Other comparisons with OpenAI Codex or Verdent

Machine-readable

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