Artificial Intelligence and Machine Learning cutoff, Eaglewood Polytechnic Institute, A.P Phulepimpalgaon
Artificial Intelligence and Machine Learning at Eaglewood Polytechnic Institute, A.P Phulepimpalgaon closed at merit 2,26,108 (9.02 percentile) in CAP 2026 Round I on open seats, 1,51,764 in the last round. Artificial Intelligence and Machine Learning got easier to get on open seats: the Round I closing merit number rose from 1,89,000 in 2025 to 2,26,108 in 2026 (a lower number is harder to get).
- CAP 2026, Round I closing
- 2,26,108 (9.02 percentile)
- CAP 2026, last round closing
- 1,51,764 (59.21 percentile)
- Seat type
- General open, other than home university
- CAP seats
- 60
- Years of data
- 2025, 2026
- Choice code
- 0263492110
| Seat type | Closing merit number | Percentile |
|---|---|---|
| General open, other than home university | 2,26,108 | 9.02 |
| Ladies open, other than home university | 1,53,840 | 58.13 |
| Economically weaker section (EWS) | 1,77,435 | 48.12 |
| CAP year | Round I | Last round |
|---|---|---|
| 2025 | 1,89,000 | 1,88,884 |
| 2026 | 2,26,108 | 1,51,764 |
Questions
What was the Artificial Intelligence and Machine Learning cutoff at Eaglewood Polytechnic Institute, A.P Phulepimpalgaon in CAP 2026?
It closed at merit 2,26,108 (9.02 percentile) in CAP 2026 Round I on open seats, 1,51,764 in the last round.
What were the category cutoffs (OBC, SC, ST, EWS, TFWS)?
Round I closing merit numbers in CAP 2026: Ladies open, other than home university 1,53,840; Economically weaker section (EWS) 1,77,435.
How many CAP seats does Artificial Intelligence and Machine Learning at Eaglewood Polytechnic Institute, A.P Phulepimpalgaon have?
60 seats in the CAP 2026 seat matrix, across all seat types.
Similar cutoffs nearby
Computer & IT engineering colleges in Jalna
Other branches at Eaglewood Polytechnic Institute, A.P Phulepimpalgaon
- Computer Engineering: 2,21,958
- Electrical Engineering: 2,27,763
- Civil Engineering: 2,29,493
Closing merit numbers from the official State CET Cell CAP lists. Past cutoffs describe what happened, not what will happen.