GFTIEast

GKCIET Malda Cutoff 2025

Ghani Khan Choudhary Institute of Engineering and Technology, Malda · Malda, West Bengal · Established 2010

Branches tracked
5
Years of data
2022–2025
Top branch 2025
Computer Science (Artificial Lntelligence and Machine Learning)
Closing rank 2025
1,47,447
Category: OPEN·Gender: Gender-Neutral·Quota: HS

Closing rank — 5-year trend

JoSAA final-round closing ranks for OPEN · Gender-Neutral. Toggle branches to compare. Rising cutoffs are normal for newer branches; a sharp fall usually signals growing demand (e.g. CSE everywhere post-2020).

Closing rank by yearLower rank = more competitive
89,8391,88,2652,86,6913,85,1174,83,5432022202320242025Computer Science (Artificial Lntelligence and Machine Learning) · 2023 · Closing rank 1,22,648Computer Science (Artificial Lntelligence and Machine Learning) · 2024 · Closing rank 1,48,356Computer Science (Artificial Lntelligence and Machine Learning) · 2025 · Closing rank 1,47,447EE · 2022 · Closing rank 1,77,312EE · 2023 · Closing rank 2,38,322EE · 2024 · Closing rank 2,92,228EE · 2025 · Closing rank 2,88,733ME · 2022 · Closing rank 1,60,967ME · 2023 · Closing rank 3,04,255ME · 2024 · Closing rank 3,56,960ME · 2025 · Closing rank 2,94,449Civil and Environmental · 2023 · Closing rank 2,35,751Civil and Environmental · 2024 · Closing rank 3,72,966Civil and Environmental · 2025 · Closing rank 4,50,734
Y-axis inverted so rank 1 sits at the top. A line sloping upward means the closing rank is falling — the branch is becoming harder to get into.

All branches at GKCIET Malda

Every branch with JoSAA final-round data, sorted by how competitive it is. YoY change compares the latest year to the previous year — negative means cutoff dropped (tougher).

BranchQuotaOpening 2025Closing 2025YoY
Computer Science (Artificial Lntelligence and Machine Learning)
Computer Science Engineering (Artificial Lntelligence and Machine Learning)
HS1,17,4491,47,447-1%
EE
Electrical Engineering
HS1,83,6352,88,733-1%
ME
Mechanical Engineering
HS2,17,0082,94,449-18%
Civil and Environmental
Civil and Environmental Engineering
HS1,64,5094,50,734+21%
Food Technology
Food Technology
HS2,56,5575,22,500-1%

Colour on YoY column: green = cutoff rose (easier), rose = cutoff fell (tougher).

Round-by-round: Computer Science (Artificial Lntelligence and Machine Learning) in 2025

JoSAA runs up to 6 rounds of counselling. The closing rank climbs each round as students upgrade or withdraw. If you're banking on R1 data, you're under-estimating your chances.

RoundOpening rankClosing rankΔ vs R1
R162,2281,10,055baseline
R282,1341,19,572+9,517 ranks
R390,4441,29,898+19,843 ranks
R490,4441,33,934+23,879 ranks
R590,4441,33,934+23,879 ranks
R61,17,4491,47,447+37,392 ranks

GKCIET Malda — frequently asked questions

What was the closing rank for Computer Science (Artificial Lntelligence and Machine Learning) at GKCIET Malda in 2025?+
The JoSAA final-round closing rank for Computer Science Engineering (Artificial Lntelligence and Machine Learning) at GKCIET Malda in 2025 was 1,47,447 for the OPEN Gender-Neutral HS quota. This is the cutoff the predictor uses by default.
Which are the toughest branches to get into at GKCIET Malda?+
Based on 2025 JoSAA final-round closing ranks (OPEN, Gender-Neutral), the most competitive branches at GKCIET Malda are: Computer Science (Artificial Lntelligence and Machine Learning) (1,47,447), EE (2,88,733), ME (2,94,449). The number in brackets is the last rank that got in.
How much does the closing rank drift between rounds at GKCIET Malda?+
For Computer Science (Artificial Lntelligence and Machine Learning) in 2025, Round 1 closed at rank 1,10,055 while the final round (R6) closed at 1,47,447. Students further from the cutoff still get in if they hold out through later rounds, so R1 data alone underestimates the real admit line.
Where does this cutoff data come from?+
Closing ranks shown here are from the official JoSAA Opening-Closing Rank (OR-CR) reports, consolidated across all rounds from 2022 through 2025. GKCIET Malda has 4 years of data in our database. The predictor uses the final round of each year to avoid over-optimistic Round 1 projections.