Grok or Claude Code: which works better with Clay?
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Clay AI agent benchmark: Grok vs Claude Code
With Clay, Grok CLI with Grok 4.6 and Claude Code both did strong GTM data work, and each fits a different job. Grok gave the most consistent results of seven agents, never moving more than 8 points between runs, and built 100-company target lists for 3 to 25 Clay credits. Claude Code with Opus 5.5 passed 14 of its 15 runs and found CMOs for under 3 credits per company, and Claude Code with Sonnet 5 scored 92 to 94 on job changes in every run.
By The Prompting Company · Snapshot November 5, 2026
The question
We ran Grok CLI with Grok 4.6, Claude Code with Opus 5.5 and Claude Code with Sonnet 5 through the same five tasks with Clay, three runs each. Clay credits are measured as the change in the Clay workspace credit balance.
Task by task
Primary score out of 100, averaged over three runs; credits are per-task averages.
| Task | Grok | Opus | Sonnet | Grok credits | Opus credits | Sonnet credits |
|---|---|---|---|---|---|---|
| Work emails | 93.0 | 86.0 | 93.0 | 339 | 392 | 374 |
| Company data | 81.5 | 90.7 | 83.5 | 405 | 894 | 612 |
| CMO | 73.0 | 79.3 | 75.0 | 776 | 289 | 1,127 |
| Job changes | 92.3 | 62.7* | 93.3 | 1,407 | 938 | 1,407 |
| Target list | 65.0 | 92.7 | 70.7 | 11 | 400 | 277 |
| All five | 81.0 | 82.3 | 83.1 | 2,937 | 2,913 | 3,797 |
*Includes one run that reached the 60-minute limit and counts as 0.
| Grok | Opus | Sonnet | |
|---|---|---|---|
| Runs passed, of 15 | 8 | 14 | 10 |
| Average model cost per reported run | $1.46 | $1.08 | $1.68 |
The three overall averages are within 2.1 points of each other.
What Grok does well with Clay
Consistency. Grok's score never moved more than 8 points between runs on any task. Added up across the five tasks, those spreads came to 19.25 points, the lowest of seven agents.
Work emails. Grok ran Clay's Work Email routine once per contact and found 93 of 100 verified emails in every run for 337.5 to 340.5 credits, about 3.4 per contact. With Clay's Work Email waterfall, you only pay credits for the provider that finds a match.
Job changes. Grok ran Enrich Person and Find Contact Details once per LinkedIn profile, at about 14 credits per person, and scored 95 in two of its three runs, catching 42 of the 45 people who had moved. Each job change run took 11.4 to 12.8 minutes.
Lean target lists. Grok built its lists from Clay's company search and spent 3, 25 and 5 credits, the lowest average of any agent on the task, 11 credits for a 100-company list. Each list had 64 to 66 qualifying companies.
Company data at about 4 credits per company. Grok averaged 405 credits for 100 companies and scored 91 on HQ country and 91 on headcount in every run.
What Claude Code does well with Clay
Runs passed. Opus passed 14 of 15 runs, the most of seven agents, and Sonnet passed 10.
CMOs. Opus used Clay's free people search to choose each CMO, then ran Work Email for that one person: 74 to 82 of 100 for 285 to 293 credits, under 3 per company. Sonnet found 79 for 302 credits with the same method.
Target lists. Opus confirmed that each company was listed in its own name and headquartered in the US before adding it, and listed 91 to 94 qualifying companies per run.
Company data and funding. Opus averaged 90.7 on company data and read funding rounds from Clay's company news, scoring 73 to 77 on funding in every run.
Job changes. Sonnet ran one enrichment per profile, decided every row and scored 92 to 94 in every run. Opus scored 94 in its second and third runs with the same method.
Which one fits which job?
| Job | Good fit | Why |
|---|---|---|
| Refreshing the same list on a schedule | Grok | Score moved at most 8 points between runs |
| Work emails | Grok or Sonnet | 93 of 100 in every run |
| Job change checks | Sonnet or Grok | Averages of 93.3 and 92.3 with one enrichment per profile |
| Low-credit target lists | Grok | 3 to 25 credits per 100-company list |
| Accuracy-first target lists | Opus | 91 to 94 qualifying companies per run |
| Finding a CMO | Opus | 74 to 82 found for under 3 credits per company |
| Funding rounds | Opus | 73 to 77 from Clay's company news |
Whichever agent you choose, name the Clay method in the prompt. For Claude Code against Codex, see "Codex or Claude Code: which works better with Clay?", and for consistency across all seven agents, "Which AI agents give consistent results with Clay?".
How we tested
Seven agents, including Grok CLI with Grok 4.6 and Claude Code with Opus 5.5 and with Sonnet 5, ran each of five tasks three times, one agent at a time, in a fresh sandbox with the same Clay key, the same 19 saved Clay routines and a 60-minute limit. A timeout counts as 0, and platform failures were rerun. Model cost is as reported by the test platform. Tasks and graders are at github.com/promptingcompany/clay-bench.
Try it yourself
The Clay Agent Plugin ships Clay's skills to your agent up front, including the habits that keep credit use down; setup is one prompt (about 15 minutes), and there is no additional cost to use it. Install the Clay Agent Plugin in Grok CLI or Claude Code, or give either a Clay API key and the Clay Public API docs. Name the method in the prompt: Work Email directly for emails, people search before any paid lookup for CMOs, and one enrichment per profile for job changes.
Common questions
Grok or Claude Code: which works better with Clay? Each fits different jobs: Grok was the most consistent agent, moving at most 8 points between runs, and Claude Code with Opus 5.5 passed the most runs, 14 of 15.
Which is better for building a target list with Clay? Grok for the lowest credit spend, 11 credits per list on average; Opus for the most qualifying companies, 91 to 94 per list.
Which is better for job change checks? Both: Sonnet scored 92 to 94 in every run and Grok 95 in two of three, each at about 14 credits per person.
Which used fewer Clay credits? Opus and Grok were close, 2,913 and 2,937 credits for one average run of all five tasks.