# DeepEval vs Gauge CLI (slim)

> DeepEval scores 61.9 (C) to Gauge CLI's 60.4 (C) for evaluations. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/deepeval-vs-gauge-cli.md (~3,950 tokens) · this version ~1,780 tokens · JSON https://www.anchorterminal.com/compare/deepeval-vs-gauge-cli.json · canonical https://www.anchorterminal.com/compare/deepeval-vs-gauge-cli
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-06
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DeepEval scores 61.9 (C) on agent readiness against Gauge CLI's 60.4 (C), and leads in 4 of 7 scored categories. Gauge CLI leads on security & auth. Both do evaluations.

- DeepEval: C 61.9, rank #526 of 1354 · https://www.anchorterminal.com/tools/deepeval.min.md
- Gauge CLI: C 60.4, rank #590 of 1354 · https://www.anchorterminal.com/tools/gauge-cli.min.md
- DeepEval, good for Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics. Ahead on Schema & documentation, 78 against 60; Payments & pricing, 60 against 40; Transparency & trust, 66 against 53. Also Free to start without a card.
- Gauge CLI, good for Teams that build skills, CLIs, SDKs or MCP servers and want to see where coding agents get stuck with them, and to test fixes before release. Ahead on Security & auth, 55 against 47. Also No key needed to call it; No incidents deducted, where DeepEval loses 3 points for them.

| Category | DeepEval | Gauge CLI |
| --- | --- | --- |
| Reliability (16%) | 59 | 60 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 78 | 60 |
| Agent ergonomics (13%) | 72 | 75 |
| Security & auth (14%) | 47 | 55 |
| Payments & pricing (10%) | 60 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 83 | 82 |
| Transparency & trust (7%) | 66 | 53 |

| Fact (where they differ) | DeepEval | Gauge CLI |
| --- | --- | --- |
| Kind | SDK + MCP | cli |
| Vendor | Confident AI, Inc. | Gauge |
| Auth | OAuth or key | None |
| Licence | Apache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own terms | MIT |
| llms.txt | yes | no |
| Last release | 2026-10-28 | 2026-11-04 |
| Popularity | 19k stars, 35k npm/wk, 736k PyPI/wk | none |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Payments & pricing, DeepEval +20: DeepEval 60 (No x402, MPP or L402 (0). DeepEval is free, and the paid option is the hosted Confident AI platform, whose prices are public without a login. Starter is $200 a month, Team $2,000 a month, and trace spans beyond the plan are $1 per GB-month (20). The framework is free and Confident AI's Free plan needs no card (20). `pip install -U deepeval` and a local run need no account, so an agent can start without a person signing up. Confident AI itself needs a browser sign-up, and its auth.md says there is no self-serve registration endpoint for API keys. Scoring this line on the local framework is a judgement call (20).); Gauge CLI 40 (Scored on the hosted option. No payment protocol (0). Credit prices weren't found on the pages read (0). Local mode is free with no card (20). Local mode needs no sign-up (20). 0 + 0 + 20 + 20 = 40.)
- Schema & documentation, DeepEval +18: DeepEval 78 (Read on the framework lines. The Python package ships `py.typed` and pydantic models, the TypeScript package ships type declarations, and the CLI is built on typer. A library has no OpenAPI file to publish (18). llms.txt on deepeval.com indexes the docs, and pages carry a Copy Markdown control (10). Each metric has its own page with required parameters and usage, and three agent skills in the repository tell a coding agent how to add evaluations and tracing (16). Typed test case and metric classes, with enums for evaluation parameters and CLI choices (12). Many runnable examples, a troubleshooting page and an environment variable reference. Error types are not listed in one place (11). Tagged releases for both packages and a public changelog by year, but the 2026 changelog still stops at 4.2.0 of 25 August on 2 November and has no entry for 4.2.1 to 4.3.2 (11).); Gauge CLI 60 (CLI reading. No machine-readable contract, -o json on read commands (10 of 25). No llms.txt; instructions bundled in the CLI for agents (5). The README says what it finds and when local or hosted fits (16 of 20). Commands with help text; typed flags (9 of 15). Worked examples, no error reference (8 of 15). Dated changelog and semver tags (12 of 15). 10 + 5 + 16 + 9 + 8 + 12 = 60.)
- Transparency & trust, DeepEval +13: DeepEval 66 (Apache-2.0 for the whole repository (30). The docs state what telemetry collects, and Confident AI publishes terms, a privacy policy, a DPA and a sub-processor list with regions. They disagree in places. The privacy policy says the DPA is available on request while it is published at /dpa, and the DeepEval docs say data sits in a private cloud on AWS while the sub-processor list names Supabase, ClickHouse and Railway for storage and hosting (20). The changelog has Breaking Change sections and the source warns at run time about the reversed metrics and the legacy key file. No deprecation policy or notice period was found (9). Telemetry through PostHog is on by default and `DEEPEVAL_TELEMETRY_OPT_OUT=1` turns it off. The source also sends the judge provider and model, the runtime kind, the CLI command and test case counts, which the docs list omits (14).); Gauge CLI 53 (MIT (30). Local data stays in .gauge/ and telemetry fields are listed; hosted data handling wasn't read (18 of 30). Dated changelog, no deprecation policy (10 of 20). Telemetry on by default, disclosed with an opt-out (20). 30 + 18 + 10 + 20 = 78.)
- Security & auth, Gauge CLI +8: DeepEval 47 (Local runs need no credential. Provider keys and `CONFIDENT_API_KEY` are read from the environment or a dotenv file, and storing keys in the legacy `.deepeval/.deepeval` file is deprecated in the source. Confident AI project keys take a name and an expiry and can be deactivated, rotated with a grace period or deleted. No per-permission scopes were found (20). The framework has no read-only mode. Once logged in, test runs and traces upload to Confident AI (8). Metrics pass application output to an LLM judge, and no guidance on untrusted content reaching the judge was found in the pages read (5). Each run is recorded in local JSON or SQLite. Confident AI documents audit log exports, which we did not read (7). GitHub shows no security policy and no published advisories, and security.txt answered 404 on both domains. No bug bounty was found. The Confident AI site states SOC 2 Type II and HIPAA, and its trust centre is drawn by script and was not read (7).); Gauge CLI 55 (Local tool. Agent credentials stay on your machine in local mode; hosted login with a device flow (20 of 30). Test agents run in fresh Docker sessions with injected inputs, and the gateway brokers credentials in hosted mode (12 of 20). Agents under test read your product's docs and outputs, with no prompt-injection guidance (5 of 15). Local transcripts and SQLite evidence per run (10 of 15). No security policy found (8 of 20). 20 + 12 + 5 + 10 + 8 = 55.)