GPT-5.4 vs Gemini 3.1 Pro for Coding

Both GPT-5.4 (released March 5, 2026) and Gemini 3.1 Pro are top-tier coding models, but they optimize for different things. Here’s how they compare for real development work.

Last verified: March 2026

Quick Comparison

Feature	GPT-5.4	Gemini 3.1 Pro
HumanEval+	95.1%	91.4%
SWE-Bench	58.2%	54.7%
MATH benchmark	88.7%	92.1% (Deep Think)
Speed (TTFT)	~1.2s	~1.4s
Context window	256K	2M
Thinking mode	GPT-5.4 Thinking	Deep Think
Coding agent	Codex	Antigravity IDE
API price (input)	$0.015/1K	$0.0125/1K

Where GPT-5.4 Wins

Speed and Iteration

GPT-5.4 is consistently faster — about 17% quicker on code generation tasks. When you’re iterating rapidly, that speed advantage compounds. You’ll complete more edit-test cycles per hour.

General Code Quality

On standard coding benchmarks (HumanEval+, MBPP, SWE-Bench), GPT-5.4 scores higher. It produces cleaner code with fewer bugs on first pass for typical web development, API work, and system programming.

Codex Agent

OpenAI’s Codex agent powered by GPT-5.4 handles multi-file refactoring, test writing, and GitHub PR workflows. The “human thinking style” reviewers mention translates to more readable code suggestions.

# GPT-5.4 excels at practical code like this
async def retry_with_backoff(fn, max_retries=3, base_delay=1.0):
    for attempt in range(max_retries):
        try:
            return await fn()
        except Exception as e:
            if attempt == max_retries - 1:
                raise
            delay = base_delay * (2 ** attempt)
            await asyncio.sleep(delay + random.uniform(0, 0.5))

Where Gemini 3.1 Pro Wins

Mathematical Programming

Gemini 3.1 Pro with Deep Think dominates when code involves complex math — optimization algorithms, scientific computing, numerical methods, and data science pipelines. The 92.1% MATH benchmark score translates directly to better mathematical code.

Long Context Understanding

With a 2M token context window vs GPT-5.4’s 256K, Gemini 3.1 Pro can ingest entire codebases. For understanding and refactoring large projects, this is a genuine advantage.

Algorithm Design

Deep Think mode excels at designing novel algorithms. When you need to implement a custom sorting algorithm, optimize a graph traversal, or build a complex state machine, Gemini often produces more elegant solutions.

# Gemini 3.1 Deep Think excels at algorithmic code
def optimal_partition(arr: list[int], k: int) -> int:
    """Minimum maximum sum when splitting arr into k partitions.
    Uses binary search on answer space — O(n log S)."""
    lo, hi = max(arr), sum(arr)
    while lo < hi:
        mid = (lo + hi) // 2
        parts, current = 1, 0
        for x in arr:
            if current + x > mid:
                parts += 1
                current = 0
            current += x
        if parts <= k:
            hi = mid
        else:
            lo = mid + 1
    return lo

IDE Integration

IDE/Tool	GPT-5.4	Gemini 3.1 Pro
Cursor	✅ Built-in	✅ Via API
GitHub Copilot	✅ Default	❌
Antigravity IDE	❌	✅ Native
Windsurf	✅ Supported	✅ Supported
Claude Code	❌ (uses Claude)	❌ (uses Claude)
VS Code	✅ Extensions	✅ Extensions

The Elephant in the Room: Claude Opus 4.6

Neither GPT-5.4 nor Gemini 3.1 Pro is the actual #1 coding model. Claude Opus 4.6 leads SWE-Bench Verified (61.4%) and HumanEval+ (94.8%, nearly matching GPT-5.4). If coding is your primary concern, Claude Opus 4.6 with Claude Code is the strongest combination.

Recommendation

Your work	Choose
Web/app development	GPT-5.4
Algorithm & math-heavy code	Gemini 3.1 Pro (Deep Think)
Large codebase refactoring	Gemini 3.1 Pro (2M context)
Rapid prototyping	GPT-5.4 (speed)
Serious software engineering	Claude Opus 4.6 (best overall)

Last verified: March 2026