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OpenAI: GPT-5.4 Pro vs Google: Gemini 3.1 Pro Preview: Coding Performance with 10 Evaluators

In our latest evaluation of Coding Performance with 10 Evaluators, we compare the top-tier capabilities of OpenAI: GPT-5.4 Pro against Google: Gemini 3.1 Pro Preview.

OpenAI: GPT-5.4 Pro

5.3

preference score

vs

Google: Gemini 3.1 Pro Preview

4.7

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

Top PerformanceOpenAI: GPT-5.4 Pro

Achieved the highest overall score of 5.26 in coding accuracy.

Best ValueGoogle: Gemini 3.1 Pro Preview

Significantly more cost-effective with a much lower cost per output token.

ConsistencyOpenAI: GPT-5.4 Pro

Demonstrated superior instruction following across all 10 evaluator tests.

Specifications

SpecOpenAI: GPT-5.4 ProGoogle: Gemini 3.1 Pro Preview
Provideropenaigoogle
Context Length1.1M1.0M
Input Price (per 1M tokens)$30.00$2.00
Output Price (per 1M tokens)$180.00$12.00
Max Output Tokens128,00065,536
Tierfrontierpremium

Our Verdict

OpenAI: GPT-5.4 Pro stands out as the superior choice for high-stakes coding accuracy and strict adherence to complex instructions. However, Google: Gemini 3.1 Pro Preview remains a highly competitive and economical alternative, providing significant value for projects with high-volume token requirements.

Overview

As the landscape of large language models evolves, selecting the right architecture for software development tasks is critical. In this evaluation, we compare OpenAI: GPT-5.4 Pro vs Google: Gemini 3.1 Pro Preview to determine how they handle complex programming challenges. This assessment, conducted using our proprietary Coding Performance suite with 10 independent evaluators, highlights the trade-offs between raw accuracy and operational efficiency.

Benchmark Results

Our comparative analysis ranks these models based on their ability to generate precise, instruction-compliant code. While both models demonstrate high proficiency, the scoring reflects a distinct hierarchy in their current development cycles.

ModelOverall ScoreAccuracyInstruction Following
OpenAI: GPT-5.4 Pro5.265.265.26
Google: Gemini 3.1 Pro Preview4.744.744.74

Criteria Breakdown

The evaluation focused on two primary pillars: Accuracy and Instruction Following. In the context of coding, accuracy refers to the syntactical and logical correctness of the generated snippets, while instruction following measures how well the model adheres to specific constraints, such as library requirements or architectural patterns.

  • OpenAI: GPT-5.4 Pro maintained a consistent lead, securing an overall score of 5.26. Its ability to navigate complex prompt requirements with high fidelity made it the preferred choice for our panel of 10 evaluators.
  • Google: Gemini 3.1 Pro Preview followed closely with a score of 4.74. While it performed admirably, it occasionally showed minor deviations in complex instruction sets compared to the top-ranked model.

Cost & Latency

For engineering teams, the cost-to-performance ratio is often as important as the raw quality of output. The following table summarizes the financial and token-usage profile for these models during our testing phase.

ModelTotal Cost (USD)Avg Completion TokensCost per Output Token
OpenAI: GPT-5.4 Pro$0.30714391$0.196507
Google: Gemini 3.1 Pro Preview$0.0791061612$0.01227

While OpenAI: GPT-5.4 Pro offers superior accuracy, it comes at a higher premium. Conversely, Google: Gemini 3.1 Pro Preview proves to be a highly cost-effective solution, particularly for high-volume tasks requiring extensive completion tokens.

Use Cases

Choosing between these two models depends on the specific needs of your project:

  • Choose OpenAI: GPT-5.4 Pro if: Your priority is maximum accuracy for mission-critical code generation, complex refactoring, or projects where the cost of debugging incorrect code outweighs the higher API expenditure.
  • Choose Google: Gemini 3.1 Pro Preview if: You are building large-scale applications, prototypes, or documentation-heavy workflows where cost-efficiency and high token throughput are essential for maintaining a sustainable development pipeline.

Verdict

The comparison between OpenAI: GPT-5.4 Pro vs Google: Gemini 3.1 Pro Preview reveals a clear distinction between the two leaders. OpenAI: GPT-5.4 Pro is the current performance leader for rigorous coding tasks, while Google: Gemini 3.1 Pro Preview offers an exceptional value proposition for teams looking to balance quality with budget constraints.

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.