Pricing

Pay per testing benchmark unit consumed

In healthcare AI development, proving safety and clinical rigor requires more than generic LLM eval sets. High-quality testing datasets with real-world physician expert annotations are difficult and expensive to source, especially at iteration speed. Harmstack helps teams validate medical AI behavior against clinically grounded benchmarks as they develop and ship.

Harmstack uses a usage-based Benchmark-as-a-Service model designed for rapid R&D iteration. Each benchmark execution consumes benchmark units, with per-unit pricing tied to the selected benchmark profile. This lets teams scale evaluation throughput from early experiments to production-grade validation.

Baseline catalogue pricing starts at 1.00 credit per benchmark unit.

1 credit = 1.00 USD for consistent budgeting across global medical AI engineering teams.

Mental Health / Psychiatry

Enterprise Benchmark-as-a-Service pricing

Baseline Catalogue Price: 1.00 USD / unit

Annual Volume Pricing - PAYG vs Annual Commitment (side by side)

TierAnnual UnitsPAYG / Unit% vs Catalogue% vs Prev PAYGPAYG Spend (Low High)Commit / Unit% Commit vs PAYG% Commit vs Catalogue% vs Prev CommitCommit Spend (Low High)
10 - 5,0001.00--$1,000 -> $5,0000.955.0%5%-$950 -> $4,750
25,001 - 10,0000.991%1.0%$4,951 -> $9,9000.936.1%7%2.1%$4,650 -> $9,300
310,001 - 25,0000.973%2.0%$9,701 -> $24,2500.907.2%10%3.2%$9,000 -> $22,500
425,001 - 100,0000.946%3.1%$23,501 -> $94,0000.868.5%14%4.4%$21,500 -> $86,000
5100,001 - 500,0000.9010%4.3%$90,001 -> $450,0000.8011.1%20%7.0%$80,000 -> $400,000
6500,001 - 1,000,0000.8515%5.6%$425,001 -> $850,0000.7215.3%28%10.0%$360,000 -> $720,000
71,000,001 - 2,000,0000.7822%8.2%$780,001 -> $1,560,0000.6319.2%37%12.5%$630,000 -> $1,260,000
82,000,001 - 5,000,0000.7030%10.3%$1,400,001 -> $3,500,0000.5225.7%48%17.5%$1,040,000 -> $2,600,000
95,000,001 - 10,000,0000.6040%14.3%$3,000,001 -> $6,000,0000.4033.3%60%23.1%$2,000,000 -> $4,000,000
1010,000,000+0.5050%16.7%$5,000,000+0.3040.0%70%25.0%$3,000,000+

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