LLM Comparison

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

Side-by-side Gemini 3.1 Pro vs GPT-5.6 Luna 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.

Rank #23 vs #27AskClash overall scores 52.9 vs 51.5.
Pricing $2.00/$12.0 vs $1.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryGoogle vs OpenAI.

Gemini 3.1 Pro vs GPT-5.6 Luna benchmark comparison

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

MetricGemini 3.1 ProGPT-5.6 Luna
Overall Score52.951.5
Leaderboard Rank#23#27
Coding Agent Index42.775.0
HLE51.4
GPQA94.3
SWE-bench80.6
SWE-Pro54.2
SWE-Atlas81.0
Terminal-Bench68.582.5
MCP Atlas69.2
Finance Agent43.0
CharXiv80.2
MMMU-Pro83.9
ARC-AGI 277.159.5
Tau299.3
MRCR84.9
Input Price (per 1M tokens)$2.00$1.00
Output Price (per 1M tokens)$12.0$6.00
Context Window1M1M
Benchmark Cells156

More Gemini 3.1 Pro and GPT-5.6 Luna comparisons

Explore how Gemini 3.1 Pro and GPT-5.6 Luna stack up against other top-ranked LLMs.

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.