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OpenAI: GPT-5.4 Mini vs DeepSeek: DeepSeek V3.2: Coding Performance with 10 Evaluators

We evaluated OpenAI: GPT-5.4 Mini vs DeepSeek: DeepSeek V3.2 to determine which model leads in coding tasks based on 10 expert evaluators.

OpenAI: GPT-5.4 Mini

7.4

preference score

vs

DeepSeek: DeepSeek V3.2

2.6

preference score

Judges ranked the responses in this Run against each other; the rank is mapped onto a 0–10 scale. It shows which response was preferred, not how good either one is — and it is not a percentage, a pass rate, or a check that the output was correct.

Sample size for this comparison was not recorded. Treat it as directional.

Evidence clarification: this article predates recorded sample provenance. Treat its conclusions as claims about the displayed examples; they do not establish general model superiority, verified correctness, or production suitability.

Key Findings

Overall PerformanceOpenAI: GPT-5.4 Mini

Scored 7.37, significantly outperforming DeepSeek's 2.63.

Instruction FollowingOpenAI: GPT-5.4 Mini

Demonstrated superior adherence to complex technical requirements.

Cost EfficiencyDeepSeek: DeepSeek V3.2

Provides a much lower cost per output token for budget-sensitive projects.

Specifications

SpecOpenAI: GPT-5.4 MiniDeepSeek: DeepSeek V3.2
Provideropenaideepseek
Context Length400K164K
Input Price (per 1M tokens)$0.75$0.27
Output Price (per 1M tokens)$4.50$0.40
Max Output Tokens128,00065,536
Tieradvancedstandard

Our Verdict

OpenAI: GPT-5.4 Mini is the clear winner for demanding coding tasks, offering superior accuracy and instruction following. While DeepSeek: DeepSeek V3.2 is significantly more cost-effective, it currently lacks the depth required to match OpenAI's output quality in this coding-specific benchmark.

Overview

In the rapidly evolving landscape of large language models, selecting the right architecture for software development tasks is critical. This report provides a detailed comparison of OpenAI: GPT-5.4 Mini vs DeepSeek: DeepSeek V3.2, focusing specifically on their Coding Performance with 10 Evaluators. By leveraging PeerLM's comparative evaluation methodology, we analyzed how these models handle complex coding instructions and output accuracy.

Benchmark Results

The comparative evaluation highlights a distinct performance gap between the two models. OpenAI: GPT-5.4 Mini emerged as the clear leader in this coding-focused suite, demonstrating a superior capability to handle technical prompts compared to DeepSeek: DeepSeek V3.2.

ModelOverall ScoreAccuracyInstruction Following
OpenAI: GPT-5.4 Mini7.377.377.37
DeepSeek: DeepSeek V3.22.632.632.63

Criteria Breakdown

Our evaluation focused on two core pillars of coding proficiency: Accuracy and Instruction Following. In the context of coding, accuracy refers to the syntactical correctness and logical soundness of the generated code, while instruction following assesses how well the model adheres to specific constraints or architectural requirements provided by the developer.

  • Accuracy: OpenAI: GPT-5.4 Mini holds a significant lead, showing a more robust understanding of programming paradigms and edge-case handling.
  • Instruction Following: The 10 evaluators consistently ranked OpenAI: GPT-5.4 Mini higher, noting its ability to maintain context throughout longer, multi-step coding tasks.

Cost & Latency

While OpenAI: GPT-5.4 Mini delivers higher performance, it is important to consider the trade-offs in cost. Below is a breakdown of the economic efficiency for both models based on the test run:

  • OpenAI: GPT-5.4 Mini: Total cost of $0.003548 with a cost per output token of $0.005501.
  • DeepSeek: DeepSeek V3.2: Total cost of $0.000447 with a cost per output token of $0.000764.

DeepSeek: DeepSeek V3.2 offers a significantly lower cost profile, which may be advantageous for high-volume, low-complexity tasks where top-tier accuracy is not the primary constraint.

Use Cases

For mission-critical applications, such as debugging complex production codebases or generating intricate microservices, OpenAI: GPT-5.4 Mini is the recommended choice due to its superior score in accuracy and instruction adherence. Conversely, DeepSeek: DeepSeek V3.2 serves as a highly economical alternative for rapid prototyping, simple script generation, or environments where budget constraints take precedence over advanced logical reasoning.

Verdict

The comparative analysis between OpenAI: GPT-5.4 Mini and DeepSeek: DeepSeek V3.2 reveals a clear hierarchy in coding performance. While DeepSeek provides an attractive cost-to-performance ratio, OpenAI: GPT-5.4 Mini remains the dominant model for developers requiring high-fidelity coding assistance.

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.

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Methodology

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