LLM Comparison

Gemini 3.7 Flash vs Grok 4.5: benchmark scores, pricing & comparison.

Side-by-side Gemini 3.7 Flash vs Grok 4.5 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 #10 vs #12AskClash overall scores 70.3 vs 68.8.
Pricing $1.50/$7.50 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryGoogle vs xAI.

Gemini 3.7 Flash vs Grok 4.5 benchmark comparison

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

MetricGemini 3.7 FlashGrok 4.5
Overall Score70.368.8
Leaderboard Rank#10#12
ACB38.957.6
RWT9.0
Coding Agent Index76.4
HLE53.640.3
GPQA94.593.1
SWE-Pro64.7
SWE-Atlas83.9
Terminal-Bench85.883.3
DeepSWE65.3
Finance Agent59.548.3
CharXiv84.5
MMMU-Pro85.580.4
ARC-AGI 252.6
MRCR97.0
Input Price (per 1M tokens)$1.50$2.00
Output Price (per 1M tokens)$7.50$6.00
Context Window1M500K
Benchmarks Published1112

Gemini 3.7 Flash vs Grok 4.5 head-to-head charts

Gemini 3.7 Flash leads 6 and Grok 4.5 leads 1 of 7 shared benchmarks. Gemini 3.7 Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Gemini 3.7 FlashGrok 4.5
Overall
70.3Gemini 3.7 Flash
68.8Grok 4.5
ACB
38.9Gemini 3.7 Flash
57.6Grok 4.5
HLE
53.6Gemini 3.7 Flash
40.3Grok 4.5
GPQA
94.5Gemini 3.7 Flash
93.1Grok 4.5
Terminal-Bench
85.8Gemini 3.7 Flash
83.3Grok 4.5
Finance Agent
59.5Gemini 3.7 Flash
48.3Grok 4.5
MMMU-Pro
85.5Gemini 3.7 Flash
80.4Grok 4.5
Gemini 3.7 Flash
Input$1.50
Output$7.50
Workload$3.00
Context1M
Grok 4.5
Input$2.00
Output$6.00
Workload$3.20
Context500K

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

More Gemini 3.7 Flash and Grok 4.5 comparisons

Explore how Gemini 3.7 Flash and Grok 4.5 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.