LLM Comparison

Grok 4.5 vs Gemini 3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side Grok 4.5 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.

Rank #5 vs #24AskClash overall scores 78.3 vs 51.9.
Pricing $2.00/$6.00 vs $2.00/$12.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryxAI vs Google.

Grok 4.5 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.

MetricGrok 4.5Gemini 3.1 Pro
Overall Score78.351.9
Leaderboard Rank#5#24
RWT9.0
Coding Agent Index76.442.7
HLE40.351.4
GPQA93.194.3
SWE-bench80.6
SWE-Pro64.754.2
SWE-Atlas83.9
Terminal-Bench83.368.5
DeepSWE11.8
MCP Atlas69.2
Finance Agent43.0
CharXiv80.2
MMMU-Pro80.483.9
ARC-AGI 277.1
Tau299.3
MRCR84.9
Input Price (per 1M tokens)$2.00$2.00
Output Price (per 1M tokens)$6.00$12.0
Context Window500K1M
Benchmarks Published916

Grok 4.5 vs Gemini 3.1 Pro head-to-head charts

Grok 4.5 leads 4 and Gemini 3.1 Pro leads 3 of 7 shared benchmarks. Grok 4.5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.5Gemini 3.1 Pro
Overall
78.3Grok 4.5
51.9Gemini 3.1 Pro
Coding Agent Index
76.4Grok 4.5
42.7Gemini 3.1 Pro
HLE
40.3Grok 4.5
51.4Gemini 3.1 Pro
GPQA
93.1Grok 4.5
94.3Gemini 3.1 Pro
SWE-Pro
64.7Grok 4.5
54.2Gemini 3.1 Pro
Terminal-Bench
83.3Grok 4.5
68.5Gemini 3.1 Pro
MMMU-Pro
80.4Grok 4.5
83.9Gemini 3.1 Pro
Grok 4.5
Input$2.00
Output$6.00
Workload$3.20
Context500K
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.

More Grok 4.5 and Gemini 3.1 Pro comparisons

Explore how Grok 4.5 and Gemini 3.1 Pro 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.