Side by side

Claude Opus 5 vs GPT-6

Up to 4 models, normalised onto the same cost basis and scored through the lens you pick.

Cost of talking
Per minute$0.096Estimate$0.012Estimate
Per hour$5.76$0.698
30-min interview$2.88$0.349
List price$15 / $75 per 1MEstimate$1.75 / $14 per 1MEstimate
Recruitment fit
Overall91/10093/100
VerdictThe best choice for rubric-based scoring, where consistency across a batch matters more than peak score.The strongest general model for hiring work — but only worth its price on the judgement-heavy steps, not on parsing.
Best for
Structured scoringBias-audit passes over model outputCandidate feedback drafting
Structured interview scoring against a rubricComparing a shortlist against a job specDrafting candidate feedback that a human will edit
Watch out for
  • Opus pricing makes it unsuitable for first-pass parsing
  • Use Haiku for the cheap steps
  • Max effort is roughly 24× the cost of Mini — do not point bulk CV parsing at it
  • A frontier model is not a fairness guarantee: you still need audited rubrics and a human on the shortlist
  • Pricing is unpublished, so total cost of ownership is unmodellable today
Capabilities
Modalitiestexttext, audio
Context window200K400K
VariantsOpus 5, Sonnet 5, Haiku 4.5Max effort, High, Medium, Low, Mini
On HumanLikeNot yetNot yet
HumanLike evals
CV field extraction (F1)0.94Estimate
Time to first token (medium effort)640 msEstimate
Published benchmarks
MMLU-ProTBDEstimate
SWE-bench VerifiedTBDEstimate

Cost per hour assumes 150 wpm and a 40% AI speaking share. Hover a figure for its full derivation.