SAT Tests
Experience authentic test-day conditions with our complete series of 4 multistage adaptive mock tests. Features built-in Desmos graphing tools, official 2h 14m module timing, and scaled 400–1600 psychometric scoring.
Digital SAT Full-Length Diagnostic Mock Test 1
Realistic multistage adaptive SAT mock exam designed to establish your baseline score across Reading, Writing, and Math.
Digital SAT Mock Test 2: High-Difficulty Adaptive Set
High-yield practice test emphasizing advanced nonlinear algebra, rhetorical synthesis, and complex scientific passage inferences.
Digital SAT Mock Test 3: Standard Form Mid-Prep Assessment
Simulates official test-day conditions with balanced difficulty across all 8 SAT domains.
Digital SAT Mock Test 4: Final Readiness Simulation
The ultimate pre-exam dress rehearsal to lock in your timing, test stamina, and final score target.
Built for Authentic Test Stamina
Why top 1500+ scorers rely on SAT.ng full-length mock exams.
Multistage Dynamic Routing
Module 2 dynamically adjusts to your real performance in Module 1, replicating the high-stakes pressure of the official exam.
Calibrated Item Weighting
Our questions are calibrated across Item Response Theory parameters to give precision score percentiles within 30 points of test day.
Deep Diagnostic Reports
Receive instant breakdowns by domain, question type, difficulty tier, and average seconds spent per question.
Tests FAQ
How often should I take a full-length SAT mock test?
We recommend taking one full mock test every 7 to 10 days during an active 8-to-12 week study schedule. This allows sufficient time to remediate errors between tests.
Are the mock tests adaptive like the official Digital SAT?
Yes. All SAT.ng mock tests utilize multistage adaptivity, routing you to either standard or high-difficulty Module 2 based on your Module 1 performance.
Can I review my past mock test attempts and mistakes?
Yes. Every completed mock exam attempt is saved to your student dashboard with a question-by-question review, time-spent telemetry, and mistake classification.