ROI & Benchmarks
Executive intro, savings math, and benchmark data for Coregit vs GitHub.
Executive intro
Coregit is a serverless Git hosting platform built for AI agents and automated workflows. One API call commits any number of files — GitHub needs 13+ calls for the same operation. This translates directly to faster agent execution and lower compute costs.
The key numbers
Commit 100 files: Coregit 19.8s vs GitHub 72.1s — 3.6x faster. One API call vs one hundred five.
Write throughput: 15,000 commits/hour vs GitHub's 38. That's 394x more capacity. GitHub's 500 writes/hour rate limit means an AI agent hits the wall after 38 ten-file commits per hour. Coregit handles 15,000 — your agent never waits.
Benchmark summary
Measured April 2026, Kazakhstan → CF edge / US-East, private repos with authentication. 10 iterations, median reported.
| Operation | GitHub | Coregit | Faster | API Calls |
|---|---|---|---|---|
| Commit 1 file | 610 ms | 1,195 ms | GitHub 2.0x | 1¹ vs 1 |
| Commit 5 files | 4,829 ms | 2,542 ms | Coregit 1.9x | 8 vs 1 |
| Commit 10 files | 8,387 ms | 4,183 ms | Coregit 2.0x | 13 vs 1 |
| Commit 100 files | 72,064 ms | 19,769 ms | Coregit 3.6x | 105 vs 1 |
| Get repo info | 426 ms | 219 ms | Coregit 1.9x | 1 vs 1 |
| Read file | 411 ms | 487 ms | GitHub 1.2x | 1 vs 1 |
| List tree | 1,290 ms | 535 ms | Coregit 2.4x | 3 vs 1 |
| List commits (20) | 397 ms | 240 ms | Coregit 1.7x | 1 vs 1 |
Full benchmark details: Scalability Benchmarks
Savings model
Single-call commits eliminate HTTP chatter
GitHub needs N+3 sequential API calls for an N-file commit (N blob creates + get HEAD + create tree + create commit + update ref). Coregit does it in 1 call.
| Workload (10-file commits/day) | GitHub API calls/day | Coregit API calls/day | Time saved/day |
|---|---|---|---|
| 100 | 1,300 | 100 | ~7 minutes |
| 1,000 | 13,000 | 1,000 | ~70 minutes |
| 10,000 | 130,000 | 10,000 | ~12 hours |
| 50,000 | 650,000 | 50,000 | ~58 hours |
Agent compute savings
AI coding agents (Cursor, Claude Code, Codex) spend compute time waiting for git operations. Faster commits = less billable agent time.
| Agent workload | GitHub wait time | Coregit wait time | Compute saved/month | $ saved (@$1.50/h) |
|---|---|---|---|---|
| 5K commits/day (10 files each) | 11.7 h/day | 5.8 h/day | 177 hours | $266 |
| 15K commits/day | 35 h/day | 17.5 h/day | 525 hours | $788 |
| 50K commits/day | 117 h/day | 58.3 h/day | 1,761 hours | $2,642 |
Seatless usage pricing
Usage tier is pay-as-you-go with no seat charges. Automation-heavy orgs with dozens of service accounts pay only for actual git operations.
| Org footprint | GitHub Team | Coregit usage | Monthly savings |
|---|---|---|---|
| 40 repos, 20 humans + 20 agents | 40 seats × $4 = $160 | ~$65 | ~$95 |
| 100 repos, 8 engineers + 52 bots | 60 seats × $4 = $240 | ~$65 | ~$175 |
Zero egress
Coregit uses object storage with zero egress costs. A team mirroring 3 TB/month of clones pays ~$270 on AWS S3 egress but $0 on Coregit.
Rate limits
GitHub: 5,000 requests/hour, 500 writes/hour (content creation). At 13 calls per 10-file commit, you hit the write limit after just 38 commits/hour.
Coregit: 15,000 requests/hour per key, 50,000/hour per org. At 1 call per commit, that's 15,000 commits/hour — 394x more throughput than GitHub's write limit.
Where each platform wins
Coregit wins on reads that aggregate data — repo info (1.9x), tree listing (2.4x), commit history (1.7x). These benefit from edge-cached flat tree maps and commit lists on the global edge network.
GitHub wins on single-file reads (1.2x) and single-op writes like create branch (1.9x). GitHub is a monolith with in-memory caches — auth, repo lookup, and file read happen in the same process with 0 network hops. Coregit is a distributed system on serverless edge compute where each component (edge cache, object storage, coordination layer, connection pooler) is a separate network call.
For multi-file writes, Coregit wins by 2-3.6x — the overhead of distributed components is amortized across one atomic call instead of GitHub's 105 sequential API calls.
Roadmap: The Session API (Zero-Wait Protocol) eliminates per-request auth overhead for agents using sessions. With the session hot layer, reads from recently-written data serve from the coordination layer (~2ms) instead of object storage (~200ms).
How to use these numbers
- For agent builders: multiply commit count × time saved to estimate compute savings
- For platform teams: compare rate limits (38 commits/hr on GitHub vs 15,000/hr on Coregit)
- For cost modeling: combine seat savings + compute savings + egress savings