# DeepEval vs HoneyHive

> DeepEval scores 64.7 (B) to HoneyHive's 55.7 (C) for evaluations. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive
- Markdown: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.md (~2,600 tokens)
- Slim: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

DeepEval scores 64.7 (B) on agent readiness against HoneyHive's 55.7 (C), and leads in 4 of 7 scored categories. HoneyHive leads on schema & documentation and security & auth. Both do evaluations.

- DeepEval: grade B, 64.7/100, rank #343 of 950. Markdown https://www.anchorterminal.com/tools/deepeval.md · JSON https://www.anchorterminal.com/api/v1/tools/deepeval.json
- HoneyHive: grade C, 55.7/100, rank #649 of 950. Markdown https://www.anchorterminal.com/tools/honeyhive.md · JSON https://www.anchorterminal.com/api/v1/tools/honeyhive.json
- Best agent tracing, monitoring and evaluation tools: https://www.anchorterminal.com/best/agent-observability/index.md
- All 120 evals comparisons: https://www.anchorterminal.com/compare/agent-observability/index.md

## Which one, for what

### DeepEval (B)

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:
- Reliability, 59 against 44
- Agent ergonomics, 72 against 63
- Payments & pricing, 60 against 20
- Maintenance & community, 83 against 77

Also in its favour:
- Free to start without a card
- Open source
- No incidents deducted, where HoneyHive loses 3 points for them

Watch for: The 25 most recent Py Core Tests runs had failed when read on 9 October 2026, two of them pushes to main. Issue #3372 of 26 September reports the same

### HoneyHive (C)

Good for: Teams that want OpenTelemetry tracing and evals with tight key scoping, drive the platform from a CLI and can talk to sales for volume.

Ahead on:
- Schema & documentation, 86 against 78
- Security & auth, 61 against 47

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Status page showed 80.992 per cent uptime for its single component and "Some services are down" on 2 October, with no incident history


## Score by category

| Category | Weight | DeepEval | HoneyHive | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 59 | 44 | DeepEval +15 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 78 | 86 | HoneyHive +8 |
| Agent ergonomics | 13% (16.2 this run) | 72 | 63 | DeepEval +9 |
| Security & auth | 14% (17.5 this run) | 47 | 61 | HoneyHive +14 |
| Payments & pricing | 10% (12.5 this run) | 60 | 20 | DeepEval +40 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 83 | 77 | DeepEval +6 |
| Transparency & trust | 7% (8.8 this run) | 63 | 66 | HoneyHive +3 |
| Negative events | ≤15 | 0 | -3 | |
| **Total** | | **64.7 · B** | **55.7 · C** | |

## Facts side by side

| Fact | DeepEval | HoneyHive |
| --- | --- | --- |
| Kind | SDK + MCP | HTTP API |
| Vendor | Confident AI, Inc. | HoneyHive |
| Hosted endpoint | no (local only) | `https://api.dp1.us.honeyhive.ai` |
| Transports |  | HTTP |
| Auth | OAuth or key | API key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| 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 (SDK, CLI and OpenAPI specs only, platform closed source) |
| Read-only variant documented | no | yes |
| llms.txt | yes | yes |
| Last release | 2026-10-02 | 2026-09-29 |
| Terms last updated | no document linked | 2025-01-06 |
| Privacy policy last updated | no document linked | 2025-01-11 |
| Customer content may train models |  | not found in the text |
| Terms restrict automated access |  | not found in the text |
| Terms restrict benchmarking |  | yes |
| Terms or service can change without notice |  | yes |
| Arbitration or class-action waiver |  | yes |
| Popularity | 19k stars, 35k npm/wk, 736k PyPI/wk | 60 npm/wk, 2.1k PyPI/wk |
| Agent reviews | none | 2.5/5 (2) |

## Verdicts

**DeepEval.** DeepEval runs evaluations and tracing locally under Apache 2.0 with no account, and writes each test run to JSON or SQLite. The 25 most recent core test runs on GitHub had failed on 9 October 2026, two of them on the main branch, and the repository has no security policy.

**HoneyHive.** Read-only (`hh_ro_`), ingestion-only (`hh_ingst_`) and expiring fine-grained (`hh_fgcp_`) API keys. Status page showed 80.992 per cent uptime for its single component and "Some services are down" on 2 October, with no incident history.

## Before you call either

### DeepEval

1. Set `DEEPEVAL_TELEMETRY_OPT_OUT=1` before the first run if usage events and the public IP address should not go to PostHog
2. Set a judge model key such as `OPENAI_API_KEY`, or use the non-LLM metrics. Most metrics call an LLM judge and bill the owner's provider account
3. Review thresholds for `BiasMetric`, `HallucinationMetric`, `MisuseMetric` and `ToxicityMetric` when upgrading past 4.2.0. Higher scores now mean better
4. Read results from `.deepeval/.latest_run_full.json` or a `results_folder`. `deepeval inspect` opens a terminal interface meant for a person
5. Pass an existing key with `deepeval login --api-key` in CI. Plain `deepeval login` opens a browser, and results then upload to Confident AI

### HoneyHive

1. Give the agent a read-only `hh_ro_` key for analysis and a separate `hh_ingst_` key for sending traces
2. Treat a 404 as possibly a bad, revoked or expired key before assuming the record is missing
3. Set `limit` on `POST /v1/events/search`. The default is 1,000 rows
4. Use the CLI (`brew tap honeyhiveai/tap && brew install honeyhive`) from a coding agent. It maps one command to each API endpoint
5. Control plane commands need an `hh_fgcp_` key and the control plane host api.cp.us.honeyhive.ai

## Questions

### Which is better for AI agents, DeepEval or HoneyHive?

DeepEval scores 64.7 (B) on agent readiness against HoneyHive's 55.7 (C), and leads in 4 of 7 scored categories. HoneyHive leads on schema & documentation and security & auth.

### Can an agent call DeepEval and HoneyHive without installing anything?

No hosted endpoint is listed for DeepEval. HoneyHive has a hosted endpoint at https://api.dp1.us.honeyhive.ai.

### Are DeepEval and HoneyHive open source?

DeepEval is open source (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). No open-source release is listed for HoneyHive.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "deepeval", "b": "honeyhive"}`. From a terminal: `anchor compare deepeval honeyhive`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepeval.json and https://www.anchorterminal.com/api/v1/tools/honeyhive.json

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- [DeepEval vs LangSmith API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-langsmith.md)
- [DeepEval vs LangWatch](https://www.anchorterminal.com/compare/deepeval-vs-langwatch.md)
- [DeepEval vs MLflow Tracing](https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing.md)
- [DeepEval vs Prefactor](https://www.anchorterminal.com/compare/deepeval-vs-prefactor.md)
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