Side by side
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 | ||
| Overall | 91/100 | 93/100 |
| Verdict | The 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 |
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| Capabilities | ||
| Modalities | text | text, audio |
| Context window | 200K | 400K |
| Variants | Opus 5, Sonnet 5, Haiku 4.5 | Max effort, High, Medium, Low, Mini |
| On HumanLike | Not yet | Not yet |
| HumanLike evals | ||
| CV field extraction (F1) | — | 0.94Estimate |
| Time to first token (medium effort) | — | 640 msEstimate |
| Published benchmarks | ||
| MMLU-Pro | — | TBDEstimate |
| SWE-bench Verified | — | TBDEstimate |
Cost per hour assumes 150 wpm and a 40% AI speaking share. Hover a figure for its full derivation.