guavaWhich AI model is best for a tech staffing firm?
Guava has no recruiting benchmark, so start with its nearest test. Claude Opus 5.5 leads MSP Bench, protecting $883,722 of $1,000,000 at a fictional managed IT provider: careful reading across messy records. It doesn’t test résumés or bias, so use it to narrow the field, then pilot on your own reqs.
The top ten on MSP Bench
Of the 15 models I’ve run, ranked by dollars protected: of the $1,000,000 that 100 hidden problems put at risk, what a model kept safe, less what it broke or wrongly called a mistake, as the mean of its runs. Claude Opus 5.5’s 9 runs ranged from $766,500 to $952,500. I built the test, and I don’t resell any of these models or take referral fees from their makers.
| # | Model | Maker | Protected | MSP Index | Index $ per task |
|---|---|---|---|---|---|
| 1 | Claude Opus 5.5 | Anthropic | $883,722 | 64 | $8.48 |
| 2 | Claude Fable 5.1 | Anthropic | $859,214 | 59 | $14.29 |
| 3 | Claude Sonnet 5.5 | Anthropic | $799,722 | 55 | $3.52 |
| 4 | GPT-6.1 Sol | OpenAI | $792,111 | 54 | $0.92 |
| 5 | GPT-6 Astra | OpenAI | $781,778 | 55 | $5.03 |
| 6 | Kimi K3.1 Pro | Moonshot AI | $767,167 | 55 | $3.88 |
| 7 | DeepSeek V4.1 Flash 1017 | DeepSeek | $727,833 | 48 | $0.42 |
| 8 | Gemini 4 Argon | $668,167 | 46 | $7.28 | |
| 9 | Muse Wonder | Meta | $642,167 | 45 | $4.43 |
| 10 | Grok 4.7 | xAI | $632,167 | 41 | $2.77 |
For the price, GPT-6.1 Sol stands out: it protects $792,111 for $1.45 a run, against $14.55 for Claude Opus 5.5. See the full leaderboard
How close is this to your desk?
- Why I’d shortlist from it It tests reading a messy folder, spotting what doesn’t add up, and not wrongly flagging what’s fine. In my judgment recruiting work asks for those habits too, but whether a good score carries over to résumés is untested.
- What it doesn’t test Résumés, requirements, your ATS or recruiting judgment. It also says nothing about bias, so test any screening model for that yourself. The AI hiring rules
How MSP Bench works
Each model gets one message from the COO of Harborline IT, a fictional managed IT provider, and one folder with everything for the business: a ticket system export, a month’s billing, device and backup reports, client user lists, a portal and scripts, contracts, staff details and the inbox. 100 problems are hidden in it, with $1,000,000 at risk between them. The MSP Index weights MSP Bench at 40% and four public benchmarks at 15% each: AA-Briefcase, AutomationBench-AA and GDP.pdf from Artificial Analysis, and the Vals Index. Read the methodology
How to choose for your desk
- Platform first Copilot, Claude Enterprise and ChatGPT Enterprise each decide which models you can use, so choose the platform first. The AI Assessment recommends one per team.
- Weigh cost per task A cheaper model can be the better buy for high-volume work like screening, if a pilot shows it holds up on your reqs. The costs in this table are the benchmark’s, and yours will differ.
- Keep a recruiter deciding AI ranks and drafts; recruiters decide, whatever the score.
- Test on your own reqs A benchmark narrows the field. A pilot on your own reqs, with a measured baseline and a check for bias, makes the call.
How Guava does it
- AI Assessment $4,000, 2 weeks. Which platform fits each team, with every workflow ranked Build, Pilot or Don’t build and an estimated monthly AI tool cost. Credited in full toward a Rollout or Implementation.
- AI Rollout $25,000, 3–6 weeks. 3–5 use cases on the platform that fits, each with a measured baseline, then hands-on training for your recruiters and account managers.
Fixed fees, agreed in writing before work starts, and you own everything built. See the engagements
Questions staffing owners ask
Does MSP Bench test recruiting?
No. It tests a fictional managed IT provider, which is further from your desk than from an MSP’s. I’d use it to narrow the field and no further.
Does a high score mean a model is safe for screening?
No. The test says nothing about bias or fair ranking. Test any screening model on your own reqs, and have your lawyer review the process.
Why rank by dollars protected?
Because problems differ in what they cost. Missing a failed backup costs far more than a typo, so the score counts the money a model kept safe, less what it broke or wrongly flagged.
Is the test public?
No. It’s private, so models can’t be trained on its answers. The MSP Bench methodology shows one example problem.
How often is it updated?
Whenever I run a new model or a new version. The date at the top of this page and of MSP Bench says when.
More questions staffing owners ask
Talk it through.
Twenty minutes on which models fit your desk. Prefer email? romeo@workwithguava.com