LLM Comparison

GPT-5.6 Terra vs GLM-5.2: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Terra vs GLM-5.2 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 #8 vs #11AskClash overall scores 76.3 vs 70.8.
Pricing $2.50/$15.0 vs $1.40/$4.40Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs Z.AI.

GPT-5.6 Terra vs GLM-5.2 benchmark comparison

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

MetricGPT-5.6 TerraGLM-5.2
Overall Score76.370.8
Leaderboard Rank#8#11
RWT8.58.5
Coding Agent Index77.074.4
HLE54.7
GPQA92.991.2
IFEval73.3
SWE-Pro63.462.1
SWE-Atlas81.074.4
Terminal-Bench87.482.7
DeepSWE69.643.8
MCP Atlas76.8
Finance Agent52.4
MMMU-Pro80.7
ARC-AGI 283.9
Tau286.399.1
MRCR89.6
Input Price (per 1M tokens)$2.50$1.40
Output Price (per 1M tokens)$15.0$4.40
Context Window1M1M
Benchmarks Published1311

GPT-5.6 Terra vs GLM-5.2 head-to-head charts

GPT-5.6 Terra leads 7 and GLM-5.2 leads 1 of 9 shared benchmarks. GLM-5.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 TerraGLM-5.2
Overall
76.3GPT-5.6 Terra
70.8GLM-5.2
RWT
8.5GPT-5.6 Terra
8.5GLM-5.2
Coding Agent Index
77.0GPT-5.6 Terra
74.4GLM-5.2
GPQA
92.9GPT-5.6 Terra
91.2GLM-5.2
SWE-Pro
63.4GPT-5.6 Terra
62.1GLM-5.2
SWE-Atlas
81.0GPT-5.6 Terra
74.4GLM-5.2
Terminal-Bench
87.4GPT-5.6 Terra
82.7GLM-5.2
DeepSWE
69.6GPT-5.6 Terra
43.8GLM-5.2
Tau2
86.3GPT-5.6 Terra
99.1GLM-5.2
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
Context1M
GLM-5.2
Input$1.40
Output$4.40
Workload$2.28
Context1M

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

More GPT-5.6 Terra and GLM-5.2 comparisons

Explore how GPT-5.6 Terra and GLM-5.2 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.