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Head to head · Evaluations · October 2026 research run

DeepEval vs W&B Weave

W&B Weave scores 66.7 (B) on agent readiness against DeepEval's 64.7 (B), and leads in 4 of 7 scored categories. DeepEval leads on payments & pricing. Both do evaluations.

Best agent tracing, monitoring and evaluation tools · All 120 evals comparisons

DeepEvalConfident AI, Inc. · SDK + MCP B64.7/100#343 of 950 W&B WeaveWeights & Biases (CoreWeave) · HTTP API B66.7/100#280 of 950

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

  • Payments & pricing, 60 against 35

Also in its favour

  • Free to start without a card

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

W&B Weave B

Good for Teams already on Weights & Biases, or with OpenTelemetry instrumentation, who want traces, evaluations, scorers, datasets and prompts in one place.

Ahead on

  • Reliability, 68 against 59
  • Security & auth, 63 against 47
  • Transparency & trust, 75 against 63

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

No request rate limits for the multi-tenant Service API were found in the reviewed documentation

Score by category

CategoryWeight this runDeepEvalW&B WeaveEdge
Reliability16%205968W&B Weave +9
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27874DeepEval +4
Agent ergonomics13%16.27271DeepEval +1
Security & auth14%17.54763W&B Weave +16
Payments & pricing10%12.56035DeepEval +25
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88387W&B Weave +4
Transparency & trust7%8.86375W&B Weave +12
Negative events≤1500
Total64.7 · B66.7 · B

Facts side by side

FactDeepEvalW&B Weave
KindSDK + MCPHTTP API
VendorConfident AI, Inc.Weights & Biases (CoreWeave)
Hosted endpointno (local only)https://trace.wandb.ai
TransportsHTTP, Streamable HTTP
AuthOAuth or keyAPI key
PricingFreemiumFreemium
x402nono
LicenceApache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own termsHosted service under the W&B Master Service Agreement. The Weave SDKs and trace server source on GitHub are Apache-2.0, and the W&B MCP server is MIT
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-022026-09-25
Terms last updatedno document linked2026-09-30
Privacy policy last updatedno document linked2026-02-24
Customer content may train modelsnot found in the text
Terms restrict automated accessyes
Terms restrict benchmarkingyes
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Popularity19k stars, 35k npm/wk, 736k PyPI/wk624k npm/wk, 219k PyPI/wk

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.

W&B Weave

The Service API at trace.wandb.ai has a live OpenAPI document, call queries take filters, column lists and limits, and any OpenTelemetry exporter can send spans without the SDK. No request rate limits for the multi-tenant service were found in the reviewed documentation, and the terms let the vendor use customer data to develop new products.

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

W&B Weave

  1. Send Authorization: Bearer <Forge API key> to https://trace.wandb.ai. Create the key at forge.coreweave.com/settings. The full secret is shown once
  2. Pass columns and limit to /calls/stream_query. Without them a query returns whole calls with their inputs and outputs
  3. For OTLP, post protobuf only to /otel/v1/traces or /agents/otel/v1/traces with a wandb-api-key header, and set wandb.entity and wandb.project as resource attributes. Spans with neither are dropped
  4. Check call.exception after .call() in the Python SDK. Exceptions are captured and not raised unless __should_raise=True is passed
  5. Treat trace inputs and outputs as untrusted text. Traces hold whatever the traced application logged

Questions

Which is better for AI agents, DeepEval or W&B Weave?

W&B Weave scores 66.7 (B) on agent readiness against DeepEval's 64.7 (B), and leads in 4 of 7 scored categories. DeepEval leads on payments & pricing.

Can an agent call DeepEval and W&B Weave without installing anything?

No hosted endpoint is listed for DeepEval. W&B Weave has a hosted endpoint at https://trace.wandb.ai.

Are DeepEval and W&B Weave open source?

Yes. 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). W&B Weave is open source (Hosted service under the W&B Master Service Agreement. The Weave SDKs and trace server source on GitHub are Apache-2.0, and the W&B MCP server is MIT).

Other comparisons with DeepEval or W&B Weave

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