PeerLM logoPeerLM
All Comparisons

OpenAI: GPT-5.2 vs xAI: Grok 4: Coding Performance with 10 Evaluators

In our latest Coding Performance with 10 Evaluators benchmark, OpenAI: GPT-5.2 significantly outperforms xAI: Grok 4 in both accuracy and cost-efficiency.

OpenAI: GPT-5.2

6.6

/ 10

vs

xAI: Grok 4

3.4

/ 10

Key Findings

Overall RankOpenAI: GPT-5.2

GPT-5.2 achieved an overall score of 6.58, nearly doubling the score of Grok 4.

Cost-EfficiencyOpenAI: GPT-5.2

GPT-5.2 is approximately 8.8x cheaper per task than Grok 4 in this coding suite.

Instruction FollowingOpenAI: GPT-5.2

GPT-5.2 demonstrated better adherence to complex coding constraints.

Specifications

SpecOpenAI: GPT-5.2xAI: Grok 4
Provideropenaix-ai
Context Length400K256K
Input Price (per 1M tokens)$1.75$3.00
Output Price (per 1M tokens)$14.00$15.00
Tieradvancedadvanced

Our Verdict

OpenAI: GPT-5.2 is the clear winner in this comparison, providing superior coding accuracy and much better cost-efficiency. While xAI: Grok 4 is a powerful model, it currently struggles to match the precision and economic value provided by GPT-5.2 for programming-focused workflows.

Overview

As the landscape of Large Language Models continues to evolve, developers are increasingly focused on finding the right tool for complex programming tasks. In this evaluation, we compare OpenAI: GPT-5.2 vs xAI: Grok 4 to determine which model leads in coding efficacy. Utilizing our PeerLM evaluation suite, we engaged 10 independent human-aligned evaluators to assess how these models handle real-world coding challenges.

Benchmark Results

The results from our Coding Performance with 10 Evaluators suite reveal a clear leader. OpenAI: GPT-5.2 secured the top rank, demonstrating a significant advantage over xAI: Grok 4 across our core metrics.

ModelOverall ScoreAccuracyInstruction FollowingTotal Cost (USD)
OpenAI: GPT-5.26.586.586.58$0.010465
xAI: Grok 43.423.423.42$0.092487

Criteria Breakdown

Our evaluation focused on two primary pillars: Accuracy and Instruction Following. Because this was a comparative, ranking-based evaluation, we prioritized how the models performed relative to one another in solving specific code-generation prompts.

  • Accuracy: OpenAI: GPT-5.2 consistently provided more syntactically correct and logical code snippets compared to xAI: Grok 4.
  • Instruction Following: GPT-5.2 demonstrated a superior ability to adhere to complex constraints within the coding prompts, whereas Grok 4 struggled to maintain context over longer generation cycles.

Cost & Latency

When analyzing the economic impact of these models, OpenAI: GPT-5.2 proves to be the highly efficient choice. Despite the similar nature of the tasks, Grok 4 resulted in significantly higher output token counts (averaging 1,363 tokens per completion), leading to a much higher total cost per request.

  • Total Cost Analysis: OpenAI: GPT-5.2 averaged a total cost of $0.010465 per set of tasks, compared to $0.092487 for xAI: Grok 4.
  • Efficiency: GPT-5.2 is not only more cost-effective but also more concise, avoiding the verbose output patterns observed in Grok 4.

Use Cases

Based on these findings, OpenAI: GPT-5.2 is the recommended model for production-grade coding applications, code refactoring, and complex software architectural tasks where instruction adherence is non-negotiable. xAI: Grok 4, while capable, may be better suited for creative exploration or tasks where token budget is less of a concern and lengthier explanations are desired.

Verdict

The comparative analysis between OpenAI: GPT-5.2 vs xAI: Grok 4 highlights a distinct performance gap. OpenAI: GPT-5.2 is the clear winner for technical tasks, offering higher accuracy and significantly better cost-efficiency for development teams.

Backed by real data

View the Full Evaluation Report

See every response, score, and evaluator judgment behind this comparison. All data from PeerLM's blind evaluation pipeline.

View Report

Run your own comparison

Test OpenAI: GPT-5.2 vs xAI: Grok 4 with your own prompts and criteria. Get results in minutes.

Start Free

Get a free managed report

We'll run a full evaluation with your real prompts and deliver a detailed recommendation. Free for qualified teams.

Request Report

Methodology

Evaluated using PeerLM's blind evaluation pipeline with 4 responses per model across 2 criteria.