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Optima vs DidWork

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Optima compared with DidWork
DetailOptima logo OptimaDidWork logo DidWork
What it doesBuild custom benchmarks to compare frontier models on performance, cost, and time efficiency for your specific tasks Independent verification for AI agent outcomes
StageNot given Startup
FoundedNot given Not given
Based inUS Not given
Pricing modelNot given Freemium
PricingToken usage for creating and running benchmarks at raw model cost. Rubric grading: $0.002 per criterion per model (standard judges) or $0.040 per criterion (premium judges), $0.10 on agentic tasks. Pairwise grading: $0.006 per match (standard, $0.150 premium), $0.015 per match on document tasks (sta Hobbyist: free forever with 250 checks/month; Pro: $9/month with 2,500 checks/month, $0.01 per extra check
Key features
  • Custom benchmark builder with example-driven task creation
  • Multiple evaluation types: Q&A, document analysis, agentic tasks, interactive conversations
  • Run benchmarks across multiple frontier models simultaneously
  • Cost and time per task metrics
  • Standard and premium judge tiers for grading
  • Rubric grading with custom criteria
  • Deterministic objective grading
  • No markup on model token costs
  • Independent outcome verification with VERIFIED, FAILED, or UNKNOWN status
  • First-party adapters for Stripe, GitHub, Linear, Sentry, Resend, and HTTP endpoints
  • MCP integration with Claude Code, Cursor, and any MCP host
  • GitHub Actions required check that fails on unverified claims
  • Audit trail storing claims, evidence, and verdicts separately
  • Capability inspection before agents call tools
  • Read-only credential access with AES-256-GCM encryption
  • Continuous monitoring with watches every 5-10 minutes on Pro plan
  • Evidence retention for 7 days on Hobbyist, 1 year on Pro
What makes it different
  • Build benchmarks on your actual tasks and data instead of standardized tests
  • Compare models across performance, cost, and time efficiency simultaneously
  • Grading expertise from major AI evaluations
  • Refuses to guess: returns UNKNOWN rather than false positives when evidence is unreachable
  • Neutral gate between agent execution and success verification
  • Runs the same way in production as in development
  • Never needs write access, only reads authoritative state
  • Structured audit trail for debugging and agent evaluation
Community votes00
DR (Domain Rating by Ahrefs)85 +1 (up) since last check2 no change since last check
Trust Flow (Majestic)281
Citation Flow (Majestic)5923
Referring domains (Majestic)1735314

4 details filled in for both companies.

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