By mid-2025, the AI “arms race” is heating up, and xAI and Anthropic have both released their flagship models, Grok 4 and Claude 4. These two models are at opposite ends of the design philosophy and deployment platform, yet they are being compared against each other as they compete head-to-head on reasoning and coding benchmarks. While Grok 4 tops the academic charts, Claude 4 is breaking the ceiling with its coding performance. So the burning question is – Grok 4 or Claude 4 – which model is better?

In this blog, we will test the performance of Grok 4 and Claude 4 on three different tasks and compare the results to find the ultimate winner!

Table of contents

• What is Grok 4?
• What is Claude 4?
• Grok 4 vs Claude 4: Performance-based comparison
• Overall Analysis
• Grok 4 vs Claude 4: Benchmark Comparison
• Conclusion
• Frequently Asked Questions

What is Grok 4?

Grok 4 is the latest multimodal large language model released by xAI, accessed via the X and available to use via the Grok app/website. Grok 4 is an agentic LLM that has been trained with tool use natively. The model is great at solving academic questions across all disciplines and surpasses almost all other LLMs on different benchmarks. Along with this, Grok 4 has incorporated a large context window with a capacity of 256k tokens, real-time web search, and an enhanced voice mode that interacts with humans with calmness. Grok 4 comes packed with great reasoning and human-like thinking capabilities, making it one of the most powerful models to date.

To know all about Grok 4, you can read this blog: Grok 4 is here, and it’s brilliant.

What is Claude 4?

Claude 4 is the most advanced large language model released by Anthropic to date. This multimodal LLM features hybrid reasoning, advanced thinking, and agent-building capacity. The model showcases lightning responses for simple queries, while for complex queries, it shifts to deeper reasoning, often breaking down a multi-step task into small tasks. It delivers performance with efficiency and records stellar results for coding problems.

Head to this blog to read about Claude 4 in detail: Claude 4 is out, and it’s amazing!

Grok 4 vs Claude 4: Performance-based comparison

Now that we have understood the nuances of the two models, let’s first look at the performance comparison of the two models:

From the graph, it’s clear that Claude 4 is beating Grok 4 in terms of response time and even the cost per task. But we don’t always have to go by numbers. Let’s test the two models for different tasks and see if the above stats hold true or not!

Task 1: SecurePay UI Prototype

Prompt: “Create an interactive and visually appealing payment gateway webpage using HTML, CSS, and JavaScript.”

Response by Grok 4

Response by Claude 4

Comparative Analysis

Claude 4 provides a comprehensive user interface with polished elements that include card, PayPal, and Apple Pay features. It also supports animations and real-time validation of the user interface. The layout of the Claude 4 models real applications like Stripe or Razorpay.

Grok 4 is also mobile-first but much more stripped down. It only supports card input with some basic validation features. It has a very simple, clean, and responsive layout.

Verdict: Both user interfaces have different use cases, as Claude 4 is best for rich presentations and showcases. Grok 4 is best for learning and building quick, interactive mobile applications.

Task 2: Physics Problem

Prompt: “Two thin circular discs of mass m and 4m, having radii of a and 2a respectively, are rigidly fixed by a massless, right rod of length ? = √(24?a) through their center. This assembly is laid on a firm and flat surface, and set rolling without slipping on the surface so that the angular speed about the axis of the rod is ω. The angular momentum of the entire assembly about the point ‘O’ is L (see the figure). Which of the following statement(s) is(are) true?

A. The magnitude of angular momentum of the assembly about its center of mass is 17?m?a2?ω?/?2
B. The magnitude of the z?component of L is 55?m?a2?ω
C. The magnitude of angular momentum of center of mass of the assembly about the point O is 81?m?a2?ω
D. The center of mass of the assembly rotates about the z?axis with an angular speed of ω/5”

Response by Grok 4

Grok 4 considers the problem with two discs of colours m and 4m attached by a rod of length √24a. It finds the centre of mass, the angle of tilt for rolling, and uses reliable sources, Vedantu and FIITJEE to verify the question from JEE Advanced 2016. Groove deduces the correct answers to be A and D, using logical deduction and valid confirmation from virtual sources in the real-world context

Response by Claude 4

Claude 4 uses a physics-based analysis guide through a stepwise thought process. It develops the centre of mass, proposes how they would roll, evaluates moment of inertia using the parallel axis theorem, provides more detail and explanation, is better for educational purposes in one regard, and theoretically than a solution alone. Claude concludes all options A-D are correct, which is incorrect, as Claude overdraws the conclusion and then arrives at accuracy in its response.

Comparative Analysis

Verdict: If you are looking for accuracy and efficiency over iteration, Grok is better because of its reasoning and the reality of whether it can use better logic than those looking to refer to only literature-supported answers. Claude offers slightly better theory in conceptual clarity, but ultimately fails in final accuracy.

Task 3: Critical Connections in a Network

Prompt: “There are n servers numbered from 0 to n – 1 connected by undirected server-to-server connections forming a network where connections[i] = [ai, bi] represents a connection between servers ai and bi. Any server can reach other servers directly or indirectly through the network.

A critical connection is a connection that, if removed, will make some servers unable to reach some other server.

Return all critical connections in the network in any order.

Input: n = 4, connections = [[0,1],[1,2],[2,0],[1,3]]

Output: [[1,3]]

Explanation: [[3,1]] is also accepted.

Example 2: Input: n = 2, connections = [[0,1]] Output: [[0,1]]”

Response by Grok 4

#include <bits .h>
using namespace std;
class Solution {
public:
   vector<vector>> criticalConnections(int n, vector<vector>>& connections) {
       vector<vector>> adj(n);
       for (auto& conn : connections) {
           adj[conn[0]].push_back(conn[1]);
           adj[conn[1]].push_back(conn[0]);
       }
       vector<int> disc(n, -1), low(n, -1), parent(n, -1);
       vector<vector>> bridges;
       int time = 0;
       function<void> dfs = [&](int u) {
           disc[u] = low[u] = time  ;
           for (int v : adj[u]) {
               if (disc[v] == -1) {  // not visited
                   parent[v] = u;
                   dfs(v);
                   low[u] = min(low[u], low[v]);
                   if (low[v] > disc[u]) {
                       bridges.push_back({u, v});
                   }
               } else if (v != parent[u]) {
                   low[u] = min(low[u], disc[v]);
               }
           }
       };
      
       for (int i = 0; i 



<h4>Response by Claude 4</h4>



<pre class="brush:php;toolbar:false">class Solution {
public:
   vector<vector>> criticalConnections(int n, vector<vector>>& connections) {
       // Build adjacency list
       vector<vector>> graph(n);
       for (auto& conn : connections) {
           graph[conn[0]].push_back(conn[1]);
           graph[conn[1]].push_back(conn[0]);
       }
       // Initialize arrays for Tarjan's algorithm
       vector<int> discovery(n, -1);  // Discovery time
       vector<int> low(n, -1);        // Low-link value
       vector<int> parent(n, -1);     // Parent in DFS tree
       vector<vector>> bridges;   // Store bridges
       int time = 0;                  // Global time counter
       // Run DFS for all unvisited nodes
       for (int i = 0; i >& graph, vector<int>& discovery,
            vector<int>& low, vector<int>& parent, vector<vector>>& bridges, int& time) {
       // Mark current node as visited
       discovery[u] = low[u] = time  ;
       // Explore all adjacent vertices
       for (int v : graph[u]) {
           if (discovery[v] == -1) {  // If v is not visited
               parent[v] = u;
               dfs(v, graph, discovery, low, parent, bridges, time);
               // Update low-link value
               low[u] = min(low[u], low[v]);
               // Check if edge u-v is a bridge
               if (low[v] > discovery[u]) {
                   bridges.push_back({u, v});
               }
           }
           else if (v != parent[u]) {  // Back edge (not parent)
               low[u] = min(low[u], discovery[v]);
           }}}};
int main() {
   Solution sol;


   int n = 5;
   vector<vector>> connections = {
       {0, 1}, {1, 2}, {2, 0}, {1, 3}, {3, 4}
   };


   vector<vector>> result = sol.criticalConnections(n, connections);


   cout 



<h3>Comparative Analysis</h3>



<p>Grok 4 and Claude 4 implement the Tarjan trunk-query algorithm in C  , but in different fashions. Claude 4 used a standard object-oriented approach. It further separated the DFS logic into a second helper method, which helped with modularization and ultimately made it a little easier to follow. This style is excellent for teaching purposes or when debugging or extending solutions to other graph problems.</p>



<p>Grok 4 used a lambda function for exploration, inside the main method. This is the most concise and modern style. It is particularly well-suited to competitive programming or small tools. It keeps the logic scoped and minimizes global side effects, but it might be a bit harder to read, especially for those new to programming.</p>



<p><strong>Final Verdict:</strong> You could rely on Claude 4 when you are trying to write code that will be readable and maintainable. You could, on the other hand, rely on Grok 4 when the priority was doing it faster and with shorter code.</p>



<h2>Overall Analysis</h2>



<p>Grok 4 focuses on accuracy, speed, and functionality in all three tasks. It is also highly proficient in real-world applicability, whether through successfully solving problems. As for Claude 4, its strengths reside in its theoretical depth, closure, and structure, making it better suited for educational or maintainable design. That said, Claude can sometimes over-reach in the analysis, which can affect the accuracy level as well.</p>




  <table>
    <thead>
      <tr>
        <td><strong>Aspect</strong></td>
        <td><strong>Grok 4</strong></td>
        <td><strong>Claude 4</strong></td>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><strong>UI Design</strong></td>
        <td>Clean, mobile-first, minimal; ideal for learning & MVPs</td>
        <td>Rich, animated, multi-option UI; great for demos & polish</td>
      </tr>
      <tr>
        <td><strong>Physics Problem</strong></td>
        <td>Accurate, logical, source-verified; answers A & D correctly</td>
        <td>Conceptually strong but incorrect (all A–D marked)</td>
      </tr>
      <tr>
        <td><strong>Graph Algorithm</strong></td>
        <td>Concise lambda-based code; best for fast coding scenarios</td>
        <td>Modular, readable code; better for education/debugging</td>
      </tr>
      <tr>
        <td><strong>Accuracy</strong></td>
        <td>High</td>
        <td>Moderate (due to overgeneralization)</td>
      </tr>
      <tr>
        <td><strong>Code Clarity</strong></td>
        <td>Moderately efficient but dense</td>
        <td>Highly easy to read and extend</td>
      </tr>
      <tr>
        <td><strong>Real-World Use</strong></td>
        <td>Excellent (CP, quick tools, accurate answers)</td>
        <td>Good (but slower and prone to over-analysis)</td>
      </tr>
      <tr>
        <td><strong>Best For</strong></td>
        <td>Speed, accuracy, compact logic</td>
        <td>Education, readability, and extensibility</td>
      </tr>
    </tbody>
  </table>





<h2>Grok 4 vs Claude 4: Benchmark Comparison</h2>



<p>In this section, we will contrast Grok 4 and Claude 4 on some major available public benchmarks. The table below illustrates their differences and some important performance metrics. Including reasoning, coding, latency, and context window size. That allows us to gauge which model performs superior in specific tasks such as technical problem solving, software development, and real-time interaction.</p>




  <table>
    <thead>
      <tr>
        <td><strong>Metric/Feature</strong></td>
        <td><strong>Grok 4 (xAI)</strong></td>
        <td><strong>Claude 4 (Sonnet 4 & Opus 4)</strong></td>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><strong>Release</strong></td>
        <td>July 2025</td>
        <td>May 2025 (Sonnet 4 & Opus 4)</td>
      </tr>
      <tr>
        <td><strong>I/O modalities</strong></td>
        <td>Text, code, voice, images</td>
        <td>Text, code, images (Vision); no built-in voice</td>
      </tr>
      <tr>
        <td><strong>HLE (Humanity’s Last Exam)</strong></td>
        <td>
<em>With tools:</em> 50.7% (new record)<em>No tools:</em> 26.9%</td>
        <td>
<em>No tools:</em> ～15–22% (typical range for GPT-4, Gemini, Claude Opus as reported)<em>With tools:</em> (not reported)</td>
      </tr>
      <tr>
        <td><strong>MMLU</strong></td>
        <td>86.6%</td>
        <td>Sonnet: 83.7%; Opus: 86.0%</td>
      </tr>
      <tr>
        <td><strong>SWE-Bench (coding)</strong></td>
        <td>72–75% (pass@1)</td>
        <td>Sonnet: 72.7%; Opus: 72.5%</td>
      </tr>
      <tr>
        <td><strong>Other Academic</strong></td>
        <td>AIME (math): 100%; GPQA (physics): 87%</td>
        <td>Comparable benchmarks not published publicly; Claude 4 focuses on coding/agent tasks</td>
      </tr>
      <tr>
        <td><strong>Latency & Speed</strong></td>
        <td>75.3 tok/s; ~5.7?s to first token</td>
        <td>Sonnet: 85.3 tok/s, 1.68?s TTFT;Opus: 64.9 tok/s, 2.58?s TTFT</td>
      </tr>
      <tr>
        <td><strong>Pricing</strong></td>
        <td>$30/mo (Standard); $300/mo (Heavy)</td>
        <td>Sonnet: $3/$15 per 1M tokens (input/output) (free tier available for Sonnet 4); Opus: $15/$75 per 1M</td>
      </tr>
      <tr>
        <td><strong>API & platforms</strong></td>
        <td>xAI API accessible via X.com/Grok apps</td>
        <td>Anthropic API; also on AWS Bedrock and Google Vertex AI</td>
      </tr>
    </tbody>
  </table>





<h2>Conclusion</h2>



<p>When comparing Grok 4 to Claude 4, I see two models that were built for different values. Grok 4 is fast, precise, and aligned with real-world use cases. Thus, great for technical programming, rapid prototyping, and problem-solving that value correctness and speed. It always provides clear, concise, and highly effective responses in areas such as UI design, engineering problems, and creating algorithms based on functional programming.</p>



<p>In contrast, Claude 4 provides strength in clarity, structure, and depth. Its education-focused and designed-for-readability coding style makes it more suitable for maintainable projects. To help impart conceptual understanding, and for teaching and debugging purposes. Nevertheless, I see that Claude may sometimes go too far in the analysis, affecting the quality of the response to the question.</p>



<p>Therefore, if your priority is raw performance and real-world application, then Grok 4 is the better choice. If your priority is clean architecture, conceptual clarity, and/or teaching and learning, then Claude 4 is your best bet.</p>



<h2>Frequently Asked Questions</h2>



<strong>Q1. Which model is overall more accurate?</strong> <p>A. Grok 4 has the better final answers across tasks performed, especially in technical resolution or real-world physics problems.?</p>  <strong>Q2. Which is better for UI or frontend coding?</strong> <p>A. Claude 4 provides much richer, polished UI output with animation and multiple methods. Grok 4 is better for mobile-first and quick prototypes.?</p>  <strong>Q3. Who should use Grok 4?</strong> <p>A. Developers, researchers, or students with an interest or need for speed, brevity, and correctness in tasks such as competitive programming, math, or quick utility tools.?</p>  <strong>Q4. Which model performs better in coding benchmarks?</strong> <p>A. Both models perform similarly on SWE-Bench (~72-75%), and Grok 4 pulled ahead (marginally) on certain reasoning benchmarks, and consistency across task completion, except drawing boxes.</p>  <strong>Q5. Can both models be used via API?</strong> <p>A. Yes, Grok 4 is available via xAI’s API and Grok apps. Claude 4 is available through Anthropic’s API.</p></vector></vector></vector></int></int></int></vector></int></int></int></vector></vector></vector>

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