Side by side

GPT-6 vs Claude Opus 5

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

Cost of talking
Per minute$0.012Estimate$0.096Estimate
Per hour$0.698$5.76
30-min interview$0.349$2.88
List price$1.75 / $14 per 1MEstimate$15 / $75 per 1MEstimate
Recruitment fit
Overall93/10091/100
VerdictThe strongest general model for hiring work — but only worth its price on the judgement-heavy steps, not on parsing.The best choice for rubric-based scoring, where consistency across a batch matters more than peak score.
Best for
Structured interview scoring against a rubricComparing a shortlist against a job specDrafting candidate feedback that a human will edit
Structured scoringBias-audit passes over model outputCandidate feedback drafting
Watch out for
  • 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  • Pricing is unpublished, so total cost of ownership is unmodellable today
  • Opus pricing makes it unsuitable for first-pass parsing
  • Use Haiku for the cheap steps
Capabilities
Modalitiestext, audiotext
Context window400K200K
VariantsMax effort, High, Medium, Low, MiniOpus 5, Sonnet 5, Haiku 4.5
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.