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Chatgpt-4.5 Vs Grok 3: Coding Comparison ????
So, Grok 3 and ChatGPT-4.5 are finally here. Two of the most advanced AI models, both claiming to be smarter, faster, and better than ever. But which one actually delivers?
Grok 3, released on February 17, 2025, is xAI’s latest model. It’s built to be more conversational, sharper at coding, and deeply integrated with X (formerly Twitter). It promises real-time insights and a more interactive experience.
ChatGPT-4.5, launched on February 27, 2025, takes reasoning, problem-solving, and memory to the next level. OpenAI calls it their most capable model yet, designed to handle technical and creative tasks with greater accuracy.
Numbers and benchmarks only tell part of the story. What really matters is how well these AIs perform in real-world scenarios. Can they solve tough coding challenges? Do they actually understand complex problems, or just generate convincing answers?
To find out, I am putting both models to the test. Let’s see which one truly stands out.
Table of Contents
- Grok 3 System Card
- ChatGPT-4.5 System Card
-
Coding Challenge
- Physics-Based Square in a Spinning Circle
- Dynamic 3D Shifting Panels Animation in JavaScript
- Modern Photo Editor App in Python
- Procedural City Skyline Generator
- Final Verdict
TL;DR
If you just want the results, Grok 3 outperforms ChatGPT-4.5 in real-world coding tasks. It delivers cleaner code, better physics simulations, and a more polished UI. ChatGPT-4.5? Not even close. It struggled with execution, gave blank screens, and felt half-baked.
And yeah, that checks out. Grok 3 is built for coding and problem-solving, while ChatGPT-4.5 is still in beta and clearly needs more work.
Grok 3 System Card
Grok 3 was released by Elon Musk’s xAI. It is designed for advanced coding tasks and logical reasoning. It focuses on code generation and debugging. It improves multi-step problem-solving and delivers faster context-aware responses.
It comes in four modes, each with a unique purpose. Grok 3 Mini is for quick answers. Grok 3 Think Mode boosts logical reasoning. Grok 3 Big Brain Mode handles complex coding. Grok 3 DeepSearch digs deep into data.
To access Grok 3 modes, users need an X Premium+ subscription, priced at $40 per month. Those who want more power can opt for SuperGrok at $30 per month, unlocking extra features.
One of its most debated features is the Unhinged Voice Mode. This gives Grok 3 a bold, sarcastic personality. Some users love the humor. Others think it makes AI unpredictable. The debate is ongoing: Should AI be fun, or should it just stick to facts?
Grok 3 performs well in benchmarks. It scored 75 in Science and leads in technical problem-solving. It got 57 in Coding and proved its programming skills.
In Math, it scored 52 and beat some models but still fell behind the best. Grok 3 Mini scored lower but held its ground against Gemini-2 Pro and DeepSeek-V3.
With fast responses, strong coding skills, and a personality that sparks debate, Grok 3 brings something different to the AI race. The real test is how well it handles actual coding challenges. That is where it must prove itself.
ChatGPT-4.5 System Card
ChatGPT-4.5 was released by OpenAI on February 27, 2025. It is designed for advanced reasoning, coding, and problem-solving. It improves memory and provides more accurate responses. It handles complex technical tasks with better efficiency.
At launch, ChatGPT-4.5 was only available for Pro users. Sam Altman later announced that it would be available for Plus users as well. ChatGPT Plus costs $20 per month and provides access to the latest model with faster responses. ChatGPT Pro costs $200 per month and offers higher usage limits with priority access.
The biggest upgrade in ChatGPT-4.5 is its ability to handle multi-step reasoning and logic-based problems. It is better at coding and debugging. It also improves data analysis and creative writing. It generates more natural and context-aware responses.
ChatGPT-4.5 is a powerful AI for developers, researchers, and businesses. Its value depends on how much reasoning, coding, and deep problem-solving matter to the user.
ChatGPT vs Grok
ChatGPT-4.5 is built on GPT-4 and GPT-4o. It has better reasoning and coding skills. OpenAI has improved its AI models over time.
Grok models are newer but improving fast. The chart shows Grok 0 launched in 2023. It was followed by Grok 1, Grok 1.5, and Grok 2. Grok 3 has made big improvements.
GPT-4o still has the highest MLU score. ChatGPT-4.5 is expected to be even better. Grok 3 is getting stronger but still needs time to catch up. ChatGPT-4.5 is ahead for now. If Grok keeps growing this fast, it might close the gap soon.
Coding Challenge
AI models are getting better at coding, but how well do they handle real-world programming challenges? To find out, I tested Grok 3 and ChatGPT-4.5 with three complex coding tasks. Each challenge requires logic, creativity, and technical skills.
1. Physics-Based Square in a Spinning Circle
Let’s see how well the AI models handle real-world physics. The task was to create a 2D simulation where a square moves inside a spinning circular container. The square needed to follow gravity, bounce off walls, and react to the spinning motion.
prompt:
Create a 2D physics simulation in Pygame where a square moves inside a spinning circular container. The square must follow gravity, collisions, and friction, reacting naturally by tumbling, sliding, and bouncing.
Grok 3 Response:
import pygame
import math
import numpy as np
# Initialize Pygame
pygame.init()
# Screen settings
WIDTH = 800
HEIGHT = 800
screen = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("Spinning Container Physics Simulation")
clock = pygame.time.Clock()
# Colors
WHITE = (255, 255, 255)
RED = (255, 0, 0)
BLUE = (0, 0, 255)
# Physics constants
GRAVITY = 0.5
FRICTION = 0.98
RESTITUTION = 0.7 # Bounce factor
class Square:
def __init__(self, x, y, size):
self.pos = np.array([float(x), float(y)])
self.vel = np.array([0.0, 0.0])
self.angle = 0.0
self.angular_vel = 0.0
self.size = size
self.mass = 1.0
self.moment_of_inertia = (self.mass * size * size) / 6.0
def get_corners(self):
# Calculate the four corners of the square based on position and angle
half_size = self.size / 2
corners = [
np.array([-half_size, -half_size]),
np.array([half_size, -half_size]),
np.array([half_size, half_size]),
np.array([-half_size, half_size])
]
# Rotate and translate corners
rotated_corners = []
for corner in corners:
rotated_x = corner[0] * math.cos(self.angle) - corner[1] * math.sin(self.angle)
rotated_y = corner[0] * math.sin(self.angle) + corner[1] * math.cos(self.angle)
rotated_corners.append(self.pos + np.array([rotated_x, rotated_y]))
return rotated_corners
def draw(self, surface, offset_angle=0):
corners = self.get_corners()
# Apply container rotation offset
rotated_corners = []
for corner in corners:
centered = corner - np.array([WIDTH/2, HEIGHT/2])
rot_x = centered[0] * math.cos(offset_angle) - centered[1] * math.sin(offset_angle)
rot_y = centered[0] * math.sin(offset_angle) + centered[1] * math.cos(offset_angle)
rotated_corners.append((rot_x + WIDTH/2, rot_y + HEIGHT/2))
pygame.draw.polygon(surface, RED, rotated_corners)
class Container:
def __init__(self, radius):
self.radius = radius
self.angle = 0.0
self.angular_vel = 0.05 # Rotation speed
def update(self):
self.angle += self.angular_vel
def draw(self, surface):
# Draw container outline
pygame.draw.circle(surface, BLUE, (WIDTH//2, HEIGHT//2), self.radius, 2)
# Draw a reference line to show rotation
end_x = WIDTH/2 + self.radius * math.cos(self.angle)
end_y = HEIGHT/2 + self.radius * math.sin(self.angle)
pygame.draw.line(surface, BLUE, (WIDTH/2, HEIGHT/2), (end_x, end_y), 2)
def handle_collision(square, container):
corners = square.get_corners()
center = np.array([WIDTH/2, HEIGHT/2])
for corner in corners:
# Distance from container center to corner
dist_vec = corner - center
dist = np.linalg.norm(dist_vec)
if dist >= container.radius:
# Collision detected
normal = dist_vec / dist # Normal vector pointing outward
penetration = dist - container.radius
# Move square back to prevent penetration
square.pos -= normal * penetration
# Reflect velocity
relative_vel = square.vel + square.angular_vel * np.array([-normal[1], normal[0]]) * square.size/2
vel_along_normal = np.dot(relative_vel, normal)
if vel_along_normal < 0: # Moving into wall
impulse = -(1 + RESTITUTION) * vel_along_normal / (1/square.mass + (square.size/2)**2/square.moment_of_inertia)
# Apply linear impulse
square.vel += impulse * normal / square.mass
# Apply angular impulse
r = corner - square.pos
cross = r[0] * normal[1] - r[1] * normal[0]
square.angular_vel += impulse * cross / square.moment_of_inertia
def main():
container = Container(300)
square = Square(WIDTH/2, HEIGHT/2 - 200, 50)
running = True
while running:
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
# Update container
container.update()
# Apply gravity (adjusted for container rotation)
gravity_dir = np.array([0, GRAVITY])
rotated_gravity = np.array([
gravity_dir[0] * math.cos(container.angle) - gravity_dir[1] * math.sin(container.angle),
gravity_dir[0] * math.sin(container.angle) + gravity_dir[1] * math.cos(container.angle)
])
square.vel += rotated_gravity
# Update square physics
square.pos += square.vel
square.angle += square.angular_vel
# Apply friction
square.vel *= FRICTION
square.angular_vel *= FRICTION
# Handle collision
handle_collision(square, container)
# Draw everything
screen.fill(WHITE)
container.draw(screen)
square.draw(screen, container.angle)
pygame.display.flip()
clock.tick(60)
pygame.quit()
if __name__ == "__main__":
main()
Here's the output of the program:
ChatGPT 4.5 Response
import pygame
import pymunk
import pymunk.pygame_util
import math
# Initialization
pygame.init()
WIDTH, HEIGHT = 800, 800
window = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("Ball in a Spinning Circle - Physics Simulation")
fps = 60
clock = pygame.time.Clock()
# Physics Setup
space = pymunk.Space()
space.gravity = (0, 980) # downward gravity (pixels per second squared)
draw_options = pymunk.pygame_util.DrawOptions(window)
# Container Parameters
circle_radius = 300
circle_thickness = 10
# Create the spinning container as a kinematic body (manually controlled rotation)
container_body = pymunk.Body(body_type=pymunk.Body.KINEMATIC)
container_body.position = WIDTH / 2, HEIGHT / 2
# Important fix: Add container_body to the physics space
space.add(container_body)
# Define the circle shape by multiple small segments (better collision detection)
segments = 60
angles_step = 2 * math.pi / segments
for i in range(segments):
angle_start = angles_step * i
angle_end = angles_step * (i + 1)
x1 = circle_radius * math.cos(angle_start)
y1 = circle_radius * math.sin(angle_start)
x2 = circle_radius * math.cos(angle_end)
y2 = circle_radius * math.sin(angle_end)
segment_shape = pymunk.Segment(container_body, (x1, y1), (x2, y2), circle_thickness)
segment_shape.elasticity = 0.8
segment_shape.friction = 0.8
space.add(segment_shape)
# Create the ball inside the container
ball_radius = 20
ball_mass = 2
ball_inertia = pymunk.moment_for_circle(ball_mass, 0, ball_radius)
ball_body = pymunk.Body(ball_mass, ball_inertia)
ball_body.position = WIDTH / 2, HEIGHT / 2
ball_shape = pymunk.Circle(ball_body, ball_radius)
ball_shape.elasticity = 0.8
ball_shape.friction = 0.6
space.add(ball_body, ball_shape)
# Simulation parameters
rotation_speed = 0.5 # radians per second
# Main loop
running = True
angle = 0
while running:
dt = clock.tick(fps) / 1000.0 # time step in seconds
# Check for quit
for event in pygame.event.get():
if event.type == pygame.QUIT:
running = False
# Spin the container continuously
angle += rotation_speed * dt
container_body.angle = angle
# Update physics simulation
space.step(dt)
# Drawing
window.fill((255, 255, 255))
space.debug_draw(draw_options) # easy built-in visual debugging
pygame.display.flip()
pygame.quit()
Here's the output of the program:
Summary
Grok 3 gave it a shot. The square bounced, spun, and reacted, even if it wasn’t perfect. ChatGPT-4.5 just dropped the square in the center like physics didn’t even matter, which was honestly disappointing.
2. Dynamic 3D Shifting Panels Animation in JavaScript
Let’s try a simple space animation and see if the AI models can handle it.
This isn’t a complex challenge, just drifting planets, soft lighting, and twinkling stars. I expected both models to get it right without issues. Grok 3 seems promising, but after ChatGPT-4.5’s last performance, I’m not too confident. Let’s see what happens.
Prompt:
Create a 3D animation of planets drifting in space using Three.js. The scene should feature a few planets of different sizes and colors, slowly moving in a natural, floating motion. Each planet should rotate gently, with soft lighting that highlights their surfaces. A glowing central star should cast light, creating subtle shadows and reflections. The background must include twinkling stars that fade in and out at different speeds, adding depth. The camera should pan slowly, providing a dynamic but smooth view of the planets without rapid movements.
Grok 3 Response
<!DOCTYPE html>
<html>
<head>
<title>Planet Animation</title>
<style>
body { margin: 0; overflow: hidden; }
canvas { display: block; }
</style>
</head>
<body>
<!-- Include Three.js from CDN -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r134/three.min.js"></script>
<script>
// Scene setup
const scene = new THREE.Scene();
const camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 0.1, 1000);
const renderer = new THREE.WebGLRenderer({ antialias: true });
renderer.setSize(window.innerWidth, window.innerHeight);
document.body.appendChild(renderer.domElement);
// Lighting
const starLight = new THREE.PointLight(0xffffff, 1.5, 100);
starLight.position.set(0, 0, 0);
scene.add(starLight);
const ambientLight = new THREE.AmbientLight(0x404040, 0.2);
scene.add(ambientLight);
// Create planets
const planets = [
{
radius: 2,
color: 0x4287f5, // Blue planet
position: new THREE.Vector3(5, 0, -10),
rotationSpeed: 0.01,
orbitSpeed: 0.002
},
{
radius: 1.5,
color: 0xf54242, // Red planet
position: new THREE.Vector3(-7, 2, -15),
rotationSpeed: 0.015,
orbitSpeed: 0.003
},
{
radius: 3,
color: 0x42f548, // Green planet
position: new THREE.Vector3(8, -1, -20),
rotationSpeed: 0.008,
orbitSpeed: 0.001
}
];
// Planet meshes
const planetMeshes = planets.map(planet => {
const geometry = new THREE.SphereGeometry(planet.radius, 32, 32);
const material = new THREE.MeshPhongMaterial({ color: planet.color });
const mesh = new THREE.Mesh(geometry, material);
mesh.position.copy(planet.position);
return { mesh, ...planet };
});
// Central star
const starGeometry = new THREE.SphereGeometry(1, 32, 32);
const starMaterial = new THREE.MeshBasicMaterial({ color: 0xffff00 });
const star = new THREE.Mesh(starGeometry, starMaterial);
scene.add(star);
// Starfield background
const starCount = 1000;
const starGeometryField = new THREE.BufferGeometry();
const starPositions = new Float32Array(starCount * 3);
const starOpacities = new Float32Array(starCount);
for (let i = 0; i < starCount; i++) {
starPositions[i * 3] = (Math.random() - 0.5) * 200;
starPositions[i * 3 + 1] = (Math.random() - 0.5) * 200;
starPositions[i * 3 + 2] = (Math.random() - 0.5) * 200;
starOpacities[i] = Math.random();
}
starGeometryField.setAttribute('position', new THREE.BufferAttribute(starPositions, 3));
starGeometryField.setAttribute('opacity', new THREE.BufferAttribute(starOpacities, 1));
const starMaterialField = new THREE.PointsMaterial({
color: 0xffffff,
size: 0.1,
transparent: true,
opacity: 0.8,
vertexColors: false
});
const starfield = new THREE.Points(starGeometryField, starMaterialField);
scene.add(starfield);
// Camera position
camera.position.set(0, 5, 15);
camera.lookAt(0, 0, 0);
// Animation
let time = 0;
function animate() {
requestAnimationFrame(animate);
// Planet rotation and orbit
planetMeshes.forEach(planet => {
scene.add(planet.mesh);
// Self rotation
planet.mesh.rotation.y += planet.rotationSpeed;
// Orbital movement
time += planet.orbitSpeed;
planet.mesh.position.x = planet.position.x * Math.cos(time) + planet.position.z * Math.sin(time);
planet.mesh.position.z = planet.position.z * Math.cos(time) - planet.position.x * Math.sin(time);
});
// Star twinkling
const opacities = starGeometryField.attributes.opacity.array;
for (let i = 0; i < starCount; i++) {
opacities[i] = Math.sin(Date.now() * 0.001 + i) * 0.5 + 0.5;
}
starGeometryField.attributes.opacity.needsUpdate = true;
// Camera panning
camera.position.x = Math.sin(Date.now() * 0.0001) * 20;
camera.position.z = Math.cos(Date.now() * 0.0001) * 15 + 10;
camera.lookAt(0, 0, 0);
renderer.render(scene, camera);
}
// Window resize handler
window.addEventListener('resize', () => {
camera.aspect = window.innerWidth / window.innerHeight;
camera.updateProjectionMatrix();
renderer.setSize(window.innerWidth, window.innerHeight);
});
animate();
</script>
</body>
</html>
Here's the output of the program:
ChatGPT 4.5 Response:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>3D Planet Scene in Three.js</title>
<style>
body, html { margin: 0; overflow: hidden; background: black; }
canvas { display: block; }
</style>
</head>
<body>
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r162/three.min.js"></script>
<script>
// Scene Setup
const scene = new THREE.Scene();
// Camera Setup
const camera = new THREE.PerspectiveCamera(
60, window.innerWidth / window.innerHeight, 0.1, 1000
);
camera.position.set(0, 5, 20);
// Renderer Setup
const renderer = new THREE.WebGLRenderer({ antialias: true });
renderer.setSize(window.innerWidth, window.innerHeight);
renderer.setPixelRatio(Math.min(window.devicePixelRatio,2));
document.body.appendChild(renderer.domElement);
// Lights
const ambient = new THREE.AmbientLight(0xffffff, 0.3);
scene.add(ambient);
const starLight = new THREE.PointLight(0xffddaa, 2, 100);
scene.add(starLight);
// Central Star
const starGeometry = new THREE.SphereGeometry(1.5, 32, 32);
const starMaterial = new THREE.MeshBasicMaterial({ color: 0xffcc66 });
const star = new THREE.Mesh(starGeometry, starMaterial);
scene.add(star);
// Planets Setup
const planets = [];
const planetData = [
{size: 0.6, color: 0x44aaff, orbitDist: 5, speed: 0.007},
{size: 1.0, color: 0xff5577, orbitDist: 8, speed: 0.005},
{size: 0.8, color: 0x33ff88, orbitDist: 11, speed: 0.003},
];
planetData.forEach((data, i) => {
const planetGeom = new THREE.SphereGeometry(data.size, 32, 32);
const planetMat = new THREE.MeshStandardMaterial({ color: data.color });
const planet = new THREE.Mesh(planetGeom, planetMat);
planet.userData = {
angle: Math.random() * Math.PI * 2,
speed: data.speed,
dist: data.orbitDist
};
planet.position.x = planet.userData.dist;
scene.add(planet);
planets.push(planet);
});
// Background Stars Setup
const starPositions = [];
const starAlphas = [];
for(let i = 0; i < 1000; i++){
starPositions.push(
THREE.MathUtils.randFloatSpread(200),
THREE.MathUtils.randFloatSpread(200),
THREE.MathUtils.randFloatSpread(200)
);
starAlphas.push(Math.random());
}
const starsGeometry = new THREE.BufferGeometry();
starsGeometry.setAttribute('position', new THREE.Float32BufferAttribute(starPositions,3));
starsGeometry.setAttribute('alpha', new THREE.Float32BufferAttribute(starAlphas,1));
const starsMaterial = new THREE.PointsMaterial({
color: 0xffffff,
transparent: true,
opacity: 0.8,
size: 0.5
});
const stars = new THREE.Points(starsGeometry, starsMaterial);
scene.add(stars);
// Animate Scene
function animate(){
requestAnimationFrame(animate);
// Planet movements and rotations
planets.forEach(planet => {
planet.userData.angle += planet.userData.speed;
planet.position.x = planet.userData.dist * Math.cos(planet.userData.angle);
planet.position.z = planet.userData.dist * Math.sin(planet.userData.angle);
planet.rotation.y += 0.002;
});
// Twinkling Stars (fade opacity)
const alphas = starsGeometry.getAttribute('alpha');
for(let i = 0; i < alphas.count; i++){
alphas.array[i] += 0.005 * (Math.random() - 0.5);
alphas.array[i] = THREE.MathUtils.clamp(alphas.array[i], 0.1, 1);
}
alphas.needsUpdate = true;
// Smooth camera pan around
const timer = Date.now() * 0.00005;
camera.position.x = 20 * Math.sin(timer);
camera.position.
