Maitraya Education Society, Nagarjuna Institute of Engineering Technology & Management, Nagpur (4192) - Cutoffs, Fees, Placements & Intake

MHT-CET CAP Round Cutoff Table

Category-wise MHT-CET cutoff scores and closing state merit ranks across CAP rounds

Civil Engineering

419219110

⇄ Scroll horizontally (6 Years)

Seat Category	Year 2026		Year 2023		Year 2022		Year 2021		Year 2020		Year 2019
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	18.02	220,005	28.38	122,496	0.64	122,333	37.43	76,261	15.72	81,420	57.68	49,214
GOBC	3.71	228,371	—	—	—	—	—	—	—	—	—	—
GSC	4.96	227,947	—	—	—	—	—	—	—	—	—	—
GST	—	—	—	—	—	—	8.34	96,484	—	—	—	—
GVJ	5.65	227,649	—	—	—	—	6.80	97,172	—	—	—	—
GNT1	—	—	—	—	—	—	17.66	90,752	—	—	33.17	62,900
TFWS	45.46	182,655	—	—	—	—	—	—	—	—	—	—
LOPEN	26.24	211,806	11.43	136,217	10.20	116,678	37.38	76,735	0.04	88,622	48.60	54,366
LOBC	24.34	213,825	—	—	5.27	119,779	—	—	—	—	—	—
LSC	7.08	227,037	—	—	—	—	—	—	—	—	—	—
LST	—	—	—	—	—	—	29.88	82,261	—	—	23.72	69,984
LNT1	5.05	227,909	—	—	—	—	—	—	—	—	—	—

Computer Science and Engineering(Artificial Intelligence and Machine Learning)

419291110

CAP Round 1

Seat Category	Year 2026
Seat Category	Cutoff Score	Merit Rank
GOPEN	44.19	185,430
GOBC	38.95	194,330
GSC	36.63	198,847
TFWS	36.64	198,609
LOPEN	39.94	193,457
LOBC	38.20	195,409
LSC	27.84	210,118
LNT1	25.43	212,616
LVJ	66.06	131,716

Mechanical Engineering

419261210

⇄ Scroll horizontally (6 Years)

Seat Category	Year 2026		Year 2023		Year 2022		Year 2021		Year 2020		Year 2019
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	38.07	195,898	42.42	108,287	4.24	120,330	8.43	96,343	13.24	82,856	7.31	83,441
GOBC	27.70	210,320	—	—	—	—	—	—	—	—	—	—
GSC	15.19	222,213	—	—	—	—	17.69	90,324	6.06	86,146	—	—
GST	30.88	206,255	—	—	—	—	30.64	81,101	—	—	—	—
GVJ	21.17	216,930	—	—	—	—	—	—	—	—	—	—
TFWS	54.97	162,270	—	—	—	—	—	—	—	—	—	—
LOPEN	31.25	205,630	—	—	—	—	29.00	82,663	—	—	35.09	61,763
LOBC	17.50	220,446	—	—	—	—	—	—	—	—	—	—
LSC	0.50	229,440	—	—	—	—	—	—	—	—	—	—
LNT1	11.01	224,847	—	—	—	—	—	—	—	—	—	—

Computer Science and Engineering

419224210

⇄ Scroll horizontally (6 Years)

Seat Category	Year 2026		Year 2023		Year 2022		Year 2021		Year 2020		Year 2019
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	60.76	146,547	44.48	105,057	39.16	92,520	41.56	72,402	14.79	81,890	63.86	45,292
GOBC	51.42	170,735	36.61	113,744	28.16	102,842	11.53	94,553	8.16	85,341	—	—
GSEBC	39.46	193,807	—	—	—	—	—	—	—	—	—	—
GSC	58.13	153,800	41.16	108,878	28.47	102,452	29.88	82,286	0.92	88,309	—	—
GST	6.04	227,472	—	—	36.72	94,039	28.77	82,979	25.04	76,537	—	—
GVJ	49.77	173,493	48.06	100,805	26.22	104,028	—	—	—	—	—	—
GNT1	26.42	211,452	18.22	131,446	38.17	93,425	—	—	—	—	—	—
GNT2	45.46	182,729	—	—	23.22	106,444	—	—	—	—	—	—
GNT3	—	—	13.84	134,530	—	—	—	—	—	—	—	—
TFWS	51.01	171,329	55.27	91,566	52.45	76,892	27.22	83,753	14.85	81,795	25.78	68,020
EWS	24.24	214,035	13.84	134,557	1.45	121,958	42.09	71,828	—	—	—	—
LOPEN	62.53	142,321	48.06	100,505	48.77	81,477	32.21	80,449	43.57	64,411	79.28	33,323
LOBC	60.27	148,036	29.24	121,865	41.48	89,688	14.96	92,366	15.72	81,432	24.80	68,923
LSC	60.92	145,980	9.09	138,204	39.16	92,380	14.92	92,759	3.71	87,228	—	—
LST	—	—	—	—	42.52	88,674	—	—	42.84	65,273	—	—
LNT2	52.72	166,823	53.65	93,427	—	—	—	—	—	—	—	—
LVJ	42.16	188,690	—	—	—	—	—	—	—	—	—	—

Electrical Engineering (Electronics and Power)

419235610

CAP Round 1

Seat Category	Year 2026
Seat Category	Cutoff Score	Merit Rank
GOPEN	24.58	213,770
GOBC	9.21	225,880
GSC	7.32	226,908
GST	31.25	205,680
GNT2	16.39	221,178
LOPEN	41.71	189,458
LOBC	20.92	217,236
LSC	15.75	221,508

Civil Engineering

0419219110

Seat Category	Year 2025		Year 2024
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	7.24	197,694	45.34	129,457
GOBC	14.31	190,288	—	—
GSC	5.81	198,987	—	—
LOPEN	15.82	188,872	32.18	147,706
LSC	—	—	16.74	165,548
LVJ	—	—	4.78	176,395

Electrical Engg [Electronics and Power]

0419235610

Seat Category	Year 2025		Year 2024
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	33.08	165,297	27.42	154,164
GOBC	32.56	166,258	19.26	162,855
GSC	17.68	186,788	—	—
GST	6.39	198,547	—	—
GNT1	3.55	201,053	—	—
TFWS	42.74	151,506	—	—
LOPEN	50.32	137,833	34.20	145,840
LOBC	21.54	182,440	2.40	178,066
LSC	0.85	203,199	—	—
LST	9.01	195,934	—	—
PWDOPEN	47.14	143,337	—	—

Computer Science and Engineering

0419224210

Seat Category	Year 2025		Year 2024
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	57.62	122,073	73.12	74,912
GOBC	54.57	128,467	60.15	103,513
GSEBC	47.14	143,015	—	—
GSC	47.89	141,335	70.87	80,344
GST	—	—	20.73	161,998
GVJ	53.68	130,970	56.56	110,899
GNT1	47.14	143,423	37.69	140,760
GNT2	41.75	152,639	48.61	124,311
TFWS	36.52	160,093	51.28	119,005
EWS	24.95	177,761	—	—
LOPEN	69.46	94,983	79.19	59,508
LOBC	63.47	109,534	64.95	94,097
LSEBC	43.53	149,555	—	—
LSC	68.49	97,031	61.64	100,150
LST	25.21	177,266	—	—
DEFOPEN	73.44	84,820	—	—
LNT1	20.64	182,898	—	—
LNT2	10.85	194,309	—	—
LNT3	69.10	95,909	—	—
LVJ	22.11	180,965	—	—
PWDOPEN	—	—	18.70	163,521

Mechanical Engineering

0419261210

Seat Category	Year 2025		Year 2024
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	24.95	177,653	50.93	120,069
GOBC	8.34	196,706	6.50	174,747
GSC	7.90	197,007	38.78	139,619
GST	0.86	203,149	42.22	134,418
GVJ	—	—	25.59	156,179
GNT3	21.62	181,979	—	—
EWS	—	—	17.34	165,032
LOPEN	28.30	173,716	—	—
LOBC	—	—	9.67	172,124

Computer Science and Engineering (Artificial Intelligence and Machine Learning)

0419291110

Seat Category	Year 2025		Year 2024
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	46.76	144,236	61.64	100,227
GOBC	35.44	163,578	59.98	104,918
GSC	28.42	173,161	61.33	100,354
GST	41.40	153,505	—	—
GVJ	26.73	174,713	19.14	163,153
GNT1	—	—	13.70	168,500
GNT3	—	—	1.91	178,350
TFWS	32.13	168,077	59.89	104,961
EWS	28.28	174,021	24.01	158,119
LOPEN	49.40	138,808	74.44	71,390
LOBC	36.12	161,364	35.67	143,105
LSEBC	52.18	133,867	—	—
LSC	32.00	168,533	36.63	142,362
LNT1	43.20	150,495	—	—

Computer Science and Engineering (Artificial Intelligence and Machine Learning)

419291110

Seat Category	Year 2023		Year 2022
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	32.88	117,904	11.44	115,555
GOBC	44.48	105,194	10.77	116,043
GSC	22.66	127,838	39.61	90,846
GST	—	—	10.77	116,099
GNT1	—	—	19.26	109,792
TFWS	52.25	95,540	12.76	114,793
EWS	59.92	83,966	—	—
LOPEN	18.13	131,521	42.02	89,316
LOBC	20.57	129,476	28.70	101,970
LSC	15.02	134,086	14.79	113,359
LST	—	—	34.67	96,730
LNT2	46.86	102,257	—	—

Electrical Engg [Electronics and Power]

419235610

⇄ Scroll horizontally (5 Years)

Seat Category	Year 2023		Year 2022		Year 2021		Year 2020		Year 2019
Seat Category	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank	Cutoff Score	Merit Rank
GOPEN	40.65	109,852	5.56	119,502	10.76	94,781	12.35	83,268	30.47	64,595
GOBC	—	—	0.55	122,393	—	—	—	—	—	—
GSC	—	—	9.24	117,225	—	—	—	—	—	—
GST	—	—	—	—	10.13	95,485	—	—	—	—
TFWS	—	—	—	—	—	—	—	—	45.12	56,333
LOPEN	34.14	116,989	29.33	101,169	32.21	80,231	60.39	50,944	68.15	42,476
LOBC	—	—	11.30	115,896	—	—	—	—	—	—
LSC	—	—	22.91	106,909	15.68	91,668	—	—	—	—
LST	—	—	5.56	119,555	30.30	81,785	—	—	—	—

Maitraya Education Society, Nagarjuna Institute of Engineering Technology & Management, Nagpur

View Multi-Year Cutoff Visualizations & Predictions

MHT-CET CAP Round Cutoff Table

Civil Engineering

Computer Science and Engineering(Artificial Intelligence and Machine Learning)

Mechanical Engineering

Computer Science and Engineering

Electrical Engineering (Electronics and Power)

Civil Engineering

Electrical Engg [Electronics and Power]

Computer Science and Engineering

Mechanical Engineering

Computer Science and Engineering (Artificial Intelligence and Machine Learning)

Computer Science and Engineering (Artificial Intelligence and Machine Learning)

Electrical Engg [Electronics and Power]