CSAB Counselling 2026: कितनी Rank तक Admission? NIT, IIIT, GFTI Cutoff #CSAB2026 #stbg #CSABCutoff

Main ideas / concepts covered

• Cutoff uncertainty + partial predictability (CSAB/CSAEAP/seat allotment rounds)

  • The speaker repeatedly addresses students’ doubt: “What cutoff will be this year? Compared to last year, up to what rank can we get admission?”
  • Core message: exact guarantees aren’t possible, but cutoffs can be predicted “to a great extent” by analyzing:
    • seat vacancies
    • past trends
    • counseling mechanics

• Mandatory processing fee / investment risk

  • Students must pay a mandatory processing fee (₹5000 mentioned) to participate in counseling (CSEAP/CSAB-related processing fee).
  • The fee is deducted whether or not a seat is ultimately obtained.

• Major misconceptions the speaker tries to correct

  1. “No good seats are left in CSE/CSC in CSAB/SEB (special rounds).”

     • Speaker’s claim: this is wrong because Computer Science & Engineering has the highest number of vacant seats among remaining branches in the special round.
     • Logic used: if a branch has the maximum vacant seats, cutoffs for that branch are likely to be more favorable.

  2. “If my branch isn’t vacant in Mock-1, I shouldn’t include it.”

     • Speaker’s argument: this is incorrect.
     • You should fill choices even if your desired seat is not vacant/visible because:
       • seats can become vacant in later rounds due to upgrades
       • a seat that becomes available later will only be allotted to students who included it in their choice list

  3. “Top NITs good branches have no chance / seats won’t shift.”

     • Speaker’s argument: shifts happen across nearly all NITs and branches.
     • Recommendation: avoid negative choice-filling.
     • Claim: CSC/Computer Science cutoffs generally shift rather than staying fixed, due to round-wise cancellations/upgrades.

• Why cutoffs can improve this year (round reduction logic)

  • Speaker claims JOSAA had fewer rounds this time (example: closed in 5 rounds, last year had 6).
  • Logic: if a later round (e.g., Round 6) doesn’t happen, those seats are effectively pushed/consumed in the next counseling stages (referenced as CSAB/CSAP-related counseling), which can make special-phase cutoffs lower/favorable.

• Behavior of candidates during choice-filling affects seat availability

  • The speaker gives a timing-based/case-study style comparison showing:
    • fewer candidates filled choices in Mock-1 this year
    • more “good allotments” even with lower competition
    • potentially different vacancy/cutoff outcomes than last year

• General guidance on choice filling strategy

  • Fill with positive hope, not negativity.
  • Don’t include only the clearly vacant seats—include broader options to capture later vacancies from upgrades.
  • Don’t be “greedy” in the most desired choices: overly optimistic/risky filling can lead to loss.
  • Use appropriate choices:
    • include only programs/branches you’d actually accept
    • don’t waste choices on unwanted branches

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Methodology / instructions explicitly conveyed (structured)

A) How to think about cutoffs and seat vacancies

• Collect data

  • Look at vacant seats by branch and category (General/EWS/OBC/SC/ST).
  • Analyze seat distributions across multiple NITs (not only one institute).

• Identify which branch has the highest vacancies

  • Speaker’s rule: if a branch family has the most vacant seats, it will likely yield the most favorable cutoffs.

• Compare with past rounds

  • Use last year’s trends (how cutoffs moved across rounds) and compare them to this year’s round structure.

B) How to fill choices in counseling (core procedural logic)

• Do not restrict choices only to seats shown as vacant in Mock.
• Always include seats you might want, even if they’re not vacant/visible in earlier rounds.

• Reasoning to apply

  • Round 1 allotment uses currently vacant seats.
  • In later rounds, students may upgrade to better choices.
  • When students upgrade, previously occupied seats may become vacant again.
  • If you didn’t include that seat in your choices, you cannot get it even if it becomes vacant later.

• Fill choices according to willingness

  • Include only programs you’d actually accept.
  • Avoid reckless “greed,” while still aiming high with a reasonable spread.

C) Predictive “ranking reach” approach

• Use category-wise estimates

  • Estimate last reachable ranks for NIT core branches (especially CSC family), then extend similarly for Triple ITs and GFTIs.

• Use round mapping logic

  • Compare JOSAA Round 5 vs last year’s Round 6.
  • Infer where those “would-have-been” seats get settled in CSAB/CSAP later rounds.

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Cutoff / rank ranges and college-type reach (as stated)

Note: The transcript is noisy and numbers may contain transcription errors; below are the rank-range claims the speaker makes.

1) NITs (approximate “last entry” ranges)

• General

  • Up to around the “last NIT” described (examples mentioned):
    • Mizoram closing around ~60,000 (General)
    • EWS around ~62,000–63,000
    • OBC before ~65,000

• SC/ST broad claims

  • SC closing around ~175,000–180,000
  • ST closing within ~2 to 2.5 lakh

• “Last NIT” examples (if considering a North-East removal logic)

  • Mentions Srinagar and other branch availability figures (values are confusing in the transcript), but the intent is that last possible ranks differ greatly by category.

2) Triple ITs (core CSE/CSC family approximate reach)

• Core CSE family

  • General: around ~55,000–65,000 (example cities: Bhagalpur, Kalyani)
  • Up to ~70,000 mentioned as possible for CSC core in that range

• EWS

  • Up to about ~80,000

• OBC

  • Up to about ~82,000

• SC

  • Possibly up to about ~2 lakh (for certain seat types)

• Additional claim

  • In some branches/places, even higher ranks are possible for specialized branches (e.g., VLSI/Mechatronics), with much larger ranges (some examples mentioned very high lakhs for ST in specific cases).

3) GFTIs (GFTI admission reach)

• For “decent” GFTIs:

  • Speaker claims core CSE/CSC-type may be possible if rank is within ~1 lakh
  • For SC/ST, broader reach mentioned:
    • up to ~2 lakh (SC)
    • up to ~4 lakh (ST) for certain structures

• Examples / references

  • Mentions named cases such as:
    • BIT Mesra
    • PEC/Chandigarh PEC
    • Chandigarh BIT Mesra references

• Very high-rank possibility (non-core, specific programs)

  • Addresses a “thumbnail question”: admissions might still be possible at very high ranks (7–12 lakh) in some specific universities/branches (examples mentioned include agriculture/animation/VFX/avionics, etc.), though not as “core CSE/major ROI” typically.

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Overall lessons the speaker emphasizes

• Vacancies and cutoffs are not fixed—they depend on round-wise allotment, upgrades, and cancellations.
• Including more relevant choices increases your chance to capture seats that become available later.
• Don’t assume absence in an early mock means impossibility—special rounds can create seats where earlier mocks show none.
• Round structure changes (fewer JOSAA rounds) can improve cutoffs in subsequent counseling phases.
• Use data + analytics rather than rumors; a major theme is predictability through research.

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Speakers / sources featured (as stated or implied)

• Sandeep Bhaiya — mentioned as “Sandeep Bhaiya from IT Guwahati” (primary speaker/host).
• ITI Guwahati — referenced as his affiliation (not a separate speaker).
• JOSAA / JEE Main counseling — referenced as the institutional process (not a person).
• CSAB / CSEAP / “SEB” counseling algorithm references — referenced as systems/processes (not a person).
• STBC’s college predictor — referenced as a third-party tool (source, not a person).