- G1.bin: 32 MB (1,048,577 G1 powers)
- G2.bin: 136 bytes (τ·G₂)
- Total: ~32 MB
- Committed:
914a952- "Reduce SRS to 1M rows (32MB) with increased Scale tier proofs"
| Tier | Monthly Proofs | Max Circuit Size | Price |
|---|---|---|---|
| Free | 250 | 32,768 rows | $0/mo |
| Pro | 500 | 262,144 rows | $39/mo |
| Scale | 1,000 | 1,048,576 rows | $149/mo |
- ✅ 50% faster loading: ~30-60 seconds (vs 60-120 seconds for 2M)
- ✅ GitHub friendly: 32MB fits comfortably (vs 64MB warning)
- ✅ More generous cap: 1,000 proofs/month (vs 250 for old Scale tier)
- ✅ Lower price: $149/mo (vs $199/mo for old 4M tier)
- ✅ Still huge capacity: 1M rows covers MNIST full, ResNet-18, small transformers
In Railway dashboard (api.tinyzkp.com service), update these variables:
# Maximum SRS capacity (1M rows)
TINYZKP_MAX_ROWS=1048576
# Tier limits
TINYZKP_FREE_MAX_ROWS=32768
TINYZKP_PRO_MAX_ROWS=262144
TINYZKP_SCALE_MAX_ROWS=1048576
# Monthly proof caps
TINYZKP_FREE_MONTHLY_CAP=250
TINYZKP_PRO_MONTHLY_CAP=500
TINYZKP_SCALE_MONTHLY_CAP=1000
# SRS file paths (already correct, but verify)
SSZKP_SRS_G1_PATH=/app/srs/G1.bin
SSZKP_SRS_G2_PATH=/app/srs/G2.binRailway will automatically:
- Pull the latest commit (
914a952) - Clone the repo with 1M SRS files
- Start the API with new env vars
Estimated deployment time: 2-3 minutes
CRITICAL: After Railway redeploys, you must manually initialize the SRS:
curl -X POST https://api.tinyzkp.com/v1/admin/srs/init \
-H "X-Admin-Token: Hartsgrove26!!" \
-H "Content-Type: application/json" \
-d '{
"max_degree": 1048576,
"mode": "production"
}'Expected response time: 30-60 seconds (loading 32MB)
Success response:
{
"message": "SRS initialized successfully",
"max_degree": 1048576,
"memory_usage_mb": 32
}Health check:
curl https://api.tinyzkp.com/v1/healthExpected:
{
"status": "ok",
"timestamp": "...",
"srs_initialized": true
}Version check:
curl https://api.tinyzkp.com/v1/versionExpected:
{
"version": "0.1.0",
"features": ["production"]
}Test proof (using your Scale account):
curl -X POST https://api.tinyzkp.com/v1/prove \
-H "X-API-Key: tz_YOUR_KEY_HERE" \
-H "Content-Type: application/json" \
-d '{
"air": {"k": 3},
"domain": {"rows": 8, "b_blk": 2, "zh_c": "1"},
"pcs": {"basis_wires": "eval"},
"witness": {
"format": "json_rows",
"rows": [[1,2,3],[2,4,6],[3,6,9],[4,8,12],[5,10,15],[6,12,18],[7,14,21],[8,16,24]]
},
"return_proof": true
}'- Railway env vars updated
- Railway redeployed with new commit
914a952 - SRS initialized via
/v1/admin/srs/init - Health check passes (
/v1/health) - Test proof generates successfully
- Version endpoint shows correct info
- Update Stripe pricing (if needed): Scale tier = $149/mo
- Update tinyzkp.com landing page:
- Scale tier: 1,048,576 rows, $149/mo, 1,000 proofs/month
- Memory efficiency: 1M rows uses only ~16KB during proving
- Use cases: MNIST full, ResNet-18, small transformers
- Cause: Loading 32MB can take 30-60 seconds
- Fix: Wait longer, or retry the initialization request
- Cause: Forgot to run manual initialization after deploy
- Fix: Run the
/v1/admin/srs/initcurl command (Step 3)
- Cause: Service crashed during startup
- Fix: Check Railway logs, verify env vars are correct
- Cause: User tried to prove >1M rows
- Fix: This is expected! Scale tier max is now 1M rows.
- Scale tier: $199/mo, 250 proofs/month, 4,194,304 rows
- Use cases: ResNet-34, BERT-base, GPT-2-medium
- File size: 128 MB
- Load time: 60-120 seconds
- Scale tier: $149/mo, 1,000 proofs/month, 1,048,576 rows
- Use cases: MNIST full, ResNet-18, small transformers
- File size: 32 MB
- Load time: 30-60 seconds
- ✅ 4× more proofs per month (1,000 vs 250)
- ✅ Lower price ($149 vs $199)
- ✅ Faster, more reliable (smaller SRS)
⚠️ 75% smaller max circuit (1M vs 4M rows)⚠️ Smaller zkML models (ResNet-18 vs ResNet-34)
Verdict: Better value for most users! 1M rows is still huge for 99% of use cases.
If you encounter issues:
- Check Railway logs
- Verify SRS initialization completed
- Test with small proof first
- Contact support with request details
Deployment Date: October 9, 2025
Commit: 914a952
Status: Ready for production deployment 🚀