Boundary Linethe marks the grades actually cost

AQA Psychology grade boundaries

In June 2026, a grade A in AQA A-level Psychology needed 205 out of 288 raw marks — 71%. An A* needed 229 (80%). That's 7 marks higher than June 2025 — the paper was found easier, so more marks were needed.

205 / 288 raw marks for a grade A · June 2026 · 71%

Boundaries, three years back

June 2026 (out of 288)

GradeRaw marksPercentage
A*22980%
A20571%
B17059%
C13547%
D10135%
E6723%

June 2025 (out of 288)

GradeRaw marksPercentage
A*22277%
A19869%
B16357%
C12844%
D9433%
E6021%

June 2024 (out of 288)

GradeRaw marksPercentage
A*22076%
A19668%
B16357%
C13045%
D9734%
E6422%
[slot: revision] — not configured. Add real, disclosed affiliate content in the property config, or delete the slot.

How far apart the grades sit (June 2026)

GapWidth
A* → A24 marks
A → B35 marks
B → C35 marks
C → D34 marks
D → E34 marks

The gap table is the revision-planning number: it's how many extra marks each grade actually costs. A gap this size is usually one exam question done properly, not a different student.

Questions

How many marks do you need for an A* in AQA Psychology?

229 out of 288 in June 2026 — 80% of the raw marks.

What percentage is an A in AQA A-level Psychology?

71% in June 2026: 205 raw marks out of 288. The percentage moves each year with the paper's difficulty — the grade is fixed, the marks aren't.

Why do grade boundaries change every year?

Boundaries are set after marking so that a grade represents the same standard despite papers varying in difficulty. A harder paper gets lower boundaries; an easier one gets higher. Predicting next year's boundary from this year's is guessing the difficulty of an unwritten paper.

Other subjects and boards

Read 18 August 2026 from the official AQA grade boundaries document: source PDF. Boundaries are set per series and never apply to next year's papers.

Boundaries read 19 August 2026 from the official board documents, linked on every page. Boundaries are set per exam series; nothing here predicts a future paper.