LLM Comparison

GPT-5.6 Sol vs Grok 4.5: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol 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 #2 vs #5AskClash overall scores 85.6 vs 78.3.
Pricing $5.00/$30.0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs xAI.

GPT-5.6 Sol vs Grok 4.5 benchmark comparison

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

MetricGPT-5.6 SolGrok 4.5
Overall Score85.678.3
Leaderboard Rank#2#5
RWT9.59.0
Coding Agent Index80.076.4
HLE47.240.3
GPQA94.193.1
SWE-Pro64.664.7
SWE-Atlas84.083.9
Terminal-Bench88.883.3
DeepSWE72.7
Finance Agent53.8
MMMU-Pro83.080.4
ARC-AGI 292.5
Tau285.1
MRCR91.5
Input Price (per 1M tokens)$5.00$2.00
Output Price (per 1M tokens)$30.0$6.00
Context Window1M500K
Benchmarks Published149

GPT-5.6 Sol vs Grok 4.5 head-to-head charts

GPT-5.6 Sol leads 8 and Grok 4.5 leads 1 of 9 shared benchmarks. Grok 4.5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolGrok 4.5
Overall
85.6GPT-5.6 Sol
78.3Grok 4.5
RWT
9.5GPT-5.6 Sol
9.0Grok 4.5
Coding Agent Index
80.0GPT-5.6 Sol
76.4Grok 4.5
HLE
47.2GPT-5.6 Sol
40.3Grok 4.5
GPQA
94.1GPT-5.6 Sol
93.1Grok 4.5
SWE-Pro
64.6GPT-5.6 Sol
64.7Grok 4.5
SWE-Atlas
84.0GPT-5.6 Sol
83.9Grok 4.5
Terminal-Bench
88.8GPT-5.6 Sol
83.3Grok 4.5
MMMU-Pro
83.0GPT-5.6 Sol
80.4Grok 4.5
GPT-5.6 Sol
Input$5.00
Output$30.0
Workload$11
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 GPT-5.6 Sol and Grok 4.5 comparisons

Explore how GPT-5.6 Sol 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.