How do GPT-5.6 Sol and Gemini 3.1 Pro compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GPT-5.6 Sol and Gemini 3.1 Pro when publicly disclosed.

LLM Comparison

GPT-5.6 Sol vs Gemini 3.1 Pro: benchmark scores, pricing & comparison.

Q: Which is better: GPT-5.6 Sol or Gemini 3.1 Pro?

AskClash compares GPT-5.6 Sol and Gemini 3.1 Pro side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, and context window so you can see which model wins on each benchmark.

Side-by-side GPT-5.6 Sol vs Gemini 3.1 Pro comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Open live leaderboard GPT-5.6 Sol model page Gemini 3.1 Pro model page

Rank #2 vs #24AskClash overall scores 85.6 vs 51.9.

Pricing $5.00/$30.0 vs $2.00/$12.0Input and output token prices per 1M tokens when published.

Proprietary vs ProprietaryOpenAI vs Google.

GPT-5.6 Sol vs Gemini 3.1 Pro benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

Metric	GPT-5.6 Sol	Gemini 3.1 Pro
Overall Score	85.6	51.9
Leaderboard Rank	#2	#24
RWT	9.5	—
Coding Agent Index	80.0	29.2
HLE	47.2	51.4
GPQA	94.1	94.3
SWE-bench	—	80.6
SWE-Pro	64.6	54.2
SWE-Atlas	84.0	—
Terminal-Bench	88.8	68.5
DeepSWE	72.7	11.8
MCP Atlas	—	69.2
Finance Agent	53.8	43.0
CharXiv	—	80.2
MMMU-Pro	83.0	83.9
ARC-AGI 2	92.5	77.1
Tau2	85.1	99.3
MRCR	91.5	84.9
Input Price (per 1M tokens)	$5.00	$2.00
Output Price (per 1M tokens)	$30.0	$12.0
Context Window	1M	1M
Benchmarks Published	14	16

GPT-5.6 Sol vs Gemini 3.1 Pro head-to-head charts

GPT-5.6 Sol leads 8 and Gemini 3.1 Pro leads 4 of 12 shared benchmarks. Gemini 3.1 Pro is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolGemini 3.1 Pro

Overall

85.6GPT-5.6 Sol

51.9Gemini 3.1 Pro

Coding Agent Index

80.0GPT-5.6 Sol

29.2Gemini 3.1 Pro

HLE

47.2GPT-5.6 Sol

51.4Gemini 3.1 Pro

GPQA

94.1GPT-5.6 Sol

94.3Gemini 3.1 Pro

SWE-Pro

64.6GPT-5.6 Sol

54.2Gemini 3.1 Pro

Terminal-Bench

88.8GPT-5.6 Sol

68.5Gemini 3.1 Pro

DeepSWE

72.7GPT-5.6 Sol

11.8Gemini 3.1 Pro

Finance Agent

53.8GPT-5.6 Sol

43.0Gemini 3.1 Pro

MMMU-Pro

83.0GPT-5.6 Sol

83.9Gemini 3.1 Pro

ARC-AGI 2

92.5GPT-5.6 Sol

77.1Gemini 3.1 Pro

Tau2

85.1GPT-5.6 Sol

99.3Gemini 3.1 Pro

MRCR

91.5GPT-5.6 Sol

84.9Gemini 3.1 Pro

GPT-5.6 Sol

Input$5.00

Output$30.0

Workload$11

Context1M

Gemini 3.1 Pro

Input$2.00

Output$12.0

Workload$4.40

Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

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How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.