guavaWhich AI model is best for an MSP?
Claude Opus 5.5, from Anthropic. On Guava’s MSP Bench, a private test of a managed IT provider with 100 hidden problems and $1,000,000 at risk, it protects the most money: $883,722 on average across its runs. The best model for your team also depends on cost per task and on the platform you already run.
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 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 team
- Platform first Copilot, Claude Enterprise and ChatGPT Enterprise each decide which models you can use, so choose the platform first. Copilot, Claude or ChatGPT?
- Weigh cost per task For high-volume work like ticket triage, a model that protects nearly as much at a fraction of the cost can be the better buy.
- Keep a tech approving Whatever the score, a tech approves every reply that goes to a client.
- Test on your own tickets A benchmark narrows the field. A pilot on your own work, with a measured baseline, 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 team training and adoption tracking.
Fixed fees, agreed in writing before work starts, and you own everything built. See the engagements
Questions MSP owners ask
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.
Does MSP Bench test Copilot itself?
No. It tests the models, not the apps around them. Copilot, Claude Enterprise and ChatGPT Enterprise add their own data access, connectors and controls, which is what a rollout sets up.
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 MSP owners ask
Talk it through.
Twenty minutes on which model and platform fit your service desk. Prefer email? romeo@workwithguava.com