LLM Comparison

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

Side-by-side Grok 4.5 vs GPT-5.6 Terra 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 #8AskClash overall scores 78.3 vs 76.3.
Pricing $2.00/$6.00 vs $2.50/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryxAI vs OpenAI.

Grok 4.5 vs GPT-5.6 Terra benchmark comparison

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

MetricGrok 4.5GPT-5.6 Terra
Overall Score78.376.3
Leaderboard Rank#5#8
RWT9.08.5
Coding Agent Index76.477.0
HLE40.3
GPQA93.192.9
SWE-Pro64.763.4
SWE-Atlas83.981.0
Terminal-Bench83.387.4
DeepSWE69.6
Finance Agent52.4
MMMU-Pro80.480.7
ARC-AGI 283.9
Tau286.3
MRCR89.6
Input Price (per 1M tokens)$2.00$2.50
Output Price (per 1M tokens)$6.00$15.0
Context Window500K1M
Benchmarks Published913

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

Grok 4.5 leads 5 and GPT-5.6 Terra leads 3 of 8 shared benchmarks. Grok 4.5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.5GPT-5.6 Terra
Overall
78.3Grok 4.5
76.3GPT-5.6 Terra
RWT
9.0Grok 4.5
8.5GPT-5.6 Terra
Coding Agent Index
76.4Grok 4.5
77.0GPT-5.6 Terra
GPQA
93.1Grok 4.5
92.9GPT-5.6 Terra
SWE-Pro
64.7Grok 4.5
63.4GPT-5.6 Terra
SWE-Atlas
83.9Grok 4.5
81.0GPT-5.6 Terra
Terminal-Bench
83.3Grok 4.5
87.4GPT-5.6 Terra
MMMU-Pro
80.4Grok 4.5
80.7GPT-5.6 Terra
Grok 4.5
Input$2.00
Output$6.00
Workload$3.20
Context500K
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
Context1M

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

More Grok 4.5 and GPT-5.6 Terra comparisons

Explore how Grok 4.5 and GPT-5.6 Terra 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.