Comprehensive cutoff breakdown for gate da: expected qualifying criteria, category-wise benchmarks, marks vs rank analysis, and target safe scores.
Specific qualifying thresholds apply for General, OBC, SC, ST, and EWS candidates.
Raw marks fluctuate with paper difficulty, but overall rank percentiles determine shortlist calls.
The GATE Data Science and Artificial Intelligence (DA) 2027 course is a structured, data-driven preparation path designed for the 100-mark, 65-question computer-based test. Unlike traditional GATE papers, the DA exam features no separate "Engineering Mathematics" section. Instead, Probability, Linear Algebra, and Calculus are examined as core subjects carrying direct sectional weight. Our curriculum enforces a strict mathematical dependency chain, ensuring you master these foundational topics before advancing to complex Machine Learning and Artificial Intelligence modules. Built specifically
GATE DA's qualifying cutoff - the minimum score needed for a valid scorecard, not for admission to a specific programme - has fallen each year since the paper launched, as the candidate pool has grown: from roughly 37.1 (General) in 2024 to 29.0 in 2025 and 26.4 in 2026. Category relaxation follows GATE's standard rule: OBC-NCL/EWS candidates qualify at approximately 90% of the General cutoff, and SC/ST/PwD candidates at roughly two-thirds of it - confirmed by the actual 2025 released figures of 29.0 (General), 26.1 (OBC-NCL/EWS), and 19.3 (SC/ST).
Because GATE DA 2027 results aren't out yet, any 2027 cutoff figure is necessarily an estimate based on this multi-year trend, not a confirmed number.
| Category | Approx. Cutoff (Indicative) | Safe Range |
|---|---|---|
| General | 25-29 | 32+ |
| OBC-NCL / EWS | 23-26 | 29+ |
| SC / ST / PwD | 17-19 | 22+ |
These indicative figures describe the qualifying threshold only. Competitive, seat-winning scores at high-demand programmes like WSAI's M.Tech in Data Science and AI run well above any of these numbers - see the Cutoff Analysis section for how to think about a genuinely "safe" admission score rather than a bare qualifying one.
The rank a given GATE DA score translates to isn't fixed by any published formula, and because DA is still building its multi-year data history (only three prior editions - 2024, 2025, 2026 - exist as of GATE 2027), a precise, DA-specific marks-to-rank table isn't as reliable as it is for decades-old papers like GATE CS or ME; treat any "marks = rank X" claim seen for DA as a rough estimate rather than a fixed conversion.
Directionally, the pattern that holds across GATE papers generally also applies here: the 40-65 mark band tends to be the most densely populated and most rank-sensitive range, where even a 2-3 mark difference can shift rank by a meaningful margin, while very high scores (75+) separate out into a much thinner, lower-competition band typically associated with the strongest institutes and, where applicable, PSU shortlists. Because DA's candidate pool is still smaller and growing year to year, rank-at-a-given-mark is also moving from year to year - a rank that corresponded to a given score in 2025 will not directly translate to 2027 as more candidates enter the paper. [NEEDS VERIFICATION: official GATE DA marks-vs-rank data by year]
Two different numbers get called "GATE DA cutoff," and conflating them is the most common mistake aspirants make. The qualifying cutoff (26.4 General in 2026, trending down from 37.1 in 2024) is simply the bar for getting a valid scorecard - it says nothing about whether that score is competitive for any specific seat. The admission cutoff - set independently by each department, often not published as a single clean number the way the qualifying cutoff is - is what actually determines whether a candidate gets an offer, and for high-demand, limited-seat programmes it typically sits well above the bare qualifying mark.
What counts as a "safe score" for GATE DA therefore depends entirely on which programme is being targeted. For a flagship, GATE-DA-exclusive programme like WSAI's M.Tech in Data Science and AI at IIT Madras - where DA is the only accepted paper and seats are limited relative to demand - a safe, competitive score is meaningfully higher than the qualifying threshold; treat any specific number quoted for this as Indicative and confirm against the department's own released admission statistics once available, since DA-specific historical admission-cutoff data is still thin. For departments that accept DA alongside other GATE papers (like IIT Hyderabad's AI department) or for NIT/IIIT-level DS/AI programmes, competitive scores tend to be comparatively more attainable, but are still institute- and year-specific.
The trend worth planning around: as DA's candidate pool keeps growing year over year, the qualifying cutoff (likely continuing a gradual downward or stabilising trend as normalisation adjusts for a larger pool) and the admission cutoffs at popular programmes (likely rising, as more well-prepared candidates compete for a still-limited number of dedicated DA-linked seats) are moving in different directions - which is exactly why "clearing the exam" and "getting a preferred seat" are two different targets to prepare for.