Best error tracking tools (buyer asking for advice)

We asked 10 models: Errors in our web app often go unnoticed until users complain. Which error tracking tool would you recommend? Each named its own top 10.

Asked 4 ways: List request · Buyer asking for advice · Search query · Worth paying for?. Share of voice pools every wording.

Agreement between models
79%
Same model, run twice
87%
Different picks
18

When agreement between models is well below a model's agreement with itself, the split reflects real differences in taste rather than randomness.

The consensus

Each cell is the position that model gave the pick; blank means it left the pick off. Click a row for each model's reasoning.

#PickScoreListed byClaude Haiku 5.5GPT-6 LunaGemini 4 ArgonQwen 3.8 FlashDeepSeek V4 ProGLM-5.3Kimi K3MiniMax M3Mistral Large 4Nemotron 3 Ultra

3 lower-scoring picks are not shown; every ballot below lists them in full.

Most divisive

Picks most models listed, at very different positions

Hot takes

Picks that appear on only one ballot

Every ballot

Hover a pick to find it on the other ballots. Marked picks appear on no other ballot.

Claude Haiku 5.5

  1. Sentry
  2. Datadog
  3. Rollbar
  4. BugSnag
  5. New Relic
  6. Honeybadger
  7. Raygun
  8. Airbrake
  9. LogRocket
  10. Elastic APM

83% with consensus · 100% self-consistent

GPT-6 Luna

  1. Sentry
  2. BugSnag
  3. Rollbar
  4. Datadog
  5. New Relic
  6. Airbrake
  7. Raygun
  8. Honeybadger
  9. Elastic APM
  10. AppSignal

87% with consensus · 92% self-consistent

Gemini 4 Argon

  1. Sentry
  2. Rollbar
  3. BugSnag
  4. Honeybadger
  5. Raygun
  6. LogRocket
  7. Datadog
  8. Airbrake
  9. New Relic
  10. TrackJS

88% with consensus · 91% self-consistent

Qwen 3.8 Flash

  1. Sentry
  2. Rollbar
  3. Raygun
  4. BugSnag
  5. Datadog
  6. New Relic
  7. Airbrake
  8. Datadog RUM
  9. LogRocket
  10. AppSignal

91% with consensus · 77% self-consistent

DeepSeek V4 Pro

  1. Sentry
  2. Datadog
  3. Rollbar
  4. BugSnag
  5. New Relic
  6. LogRocket
  7. Raygun
  8. Airbrake
  9. Honeycomb
  10. FullStory

82% with consensus · 80% self-consistent

GLM-5.3

  1. Sentry
  2. Rollbar
  3. Datadog
  4. BugSnag
  5. Raygun
  6. New Relic
  7. Airbrake
  8. Honeybadger
  9. LogRocket
  10. GlitchTip

94% with consensus · 85% self-consistent

Kimi K3

  1. Sentry
  2. Rollbar
  3. BugSnag
  4. Raygun
  5. LogRocket
  6. Datadog RUM
  7. Airbrake
  8. New Relic
  9. Datadog
  10. Honeybadger

88% with consensus · 80% self-consistent

MiniMax M3

  1. Sentry
  2. BugSnag
  3. Rollbar
  4. Raygun
  5. Airbrake
  6. Honeybadger
  7. Datadog
  8. New Relic
  9. LogRocket
  10. Atlassian Jira

83% with consensus · 87% self-consistent

Mistral Large 4

  1. Sentry
  2. Datadog
  3. BugSnag
  4. Rollbar
  5. LogRocket
  6. Raygun
  7. New Relic
  8. Airbrake
  9. GlitchTip
  10. Grafana Faro

82% with consensus · 90% self-consistent

Nemotron 3 Ultra

  1. Sentry
  2. Datadog
  3. New Relic
  4. Rollbar
  5. BugSnag
  6. Airbrake
  7. Honeybadger
  8. Raygun
  9. LogRocket
  10. Elastic APM

76% with consensus · 96% self-consistent

Who agrees with whom

Overlap between two models' lists, weighted toward the top · 100 means identical · Color runs from 64 (lightest) to 95 (darkest)

Claude Haiku 5.5GPT-6 LunaGemini 4 ArgonQwen 3.8 FlashDeepSeek V4 ProGLM-5.3Kimi K3MiniMax M3Mistral Large 4Nemotron 3 Ultra
Claude Haiku 5.5857679958871778790
GPT-6 Luna857779828475877980
Gemini 4 Argon767782758488847767
Qwen 3.8 Flash797982799087807572
DeepSeek V4 Pro958275798674729086
GLM-5.3888484908683798281
Kimi K3717588877483837764
MiniMax M3778784807279837470
Mistral Large 4877977759082777483
Nemotron 3 Ultra908067728681647083