How do GLM-5.2 and DeepSeek V4 Pro (Max) compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GLM-5.2 and DeepSeek V4 Pro (Max) when publicly disclosed.

LLM Comparison

GLM-5.2 vs DeepSeek V4 Pro (Max): benchmark scores, pricing & comparison.

Q: Which is better: GLM-5.2 or DeepSeek V4 Pro (Max)?

AskClash compares GLM-5.2 and DeepSeek V4 Pro (Max) side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, and context window so you can see which model wins on each benchmark.

Side-by-side GLM-5.2 vs DeepSeek V4 Pro (Max) 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.

Open live leaderboard GLM-5.2 model page DeepSeek V4 Pro (Max) model page

Rank #18 vs #30AskClash overall scores 54.2 vs 41.0.

Pricing $1.40/$4.40 vs $0.43/$0.87Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightZ.AI vs DeepSeek.

GLM-5.2 vs DeepSeek V4 Pro (Max) benchmark comparison

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

Metric	GLM-5.2	DeepSeek V4 Pro (Max)
Overall Score	54.2	41.0
Leaderboard Rank	#18	#30
RWT	8.5	7.0
Coding Agent Index	74.4	—
HLE	54.7	37.7
GPQA	91.2	90.1
MATH-500	—	64.5
IFEval	73.3	—
SWE-bench	—	80.6
SWE-Pro	62.1	55.4
SWE-Atlas	74.4	—
Terminal-Bench	82.7	67.9
DeepSWE	43.8	—
MCP Atlas	76.8	73.6
Tau2	99.1	96.2
MRCR	—	83.5
Input Price (per 1M tokens)	$1.40	$0.43
Output Price (per 1M tokens)	$4.40	$0.87
Context Window	1M	1M
Benchmarks Published	11	9

GLM-5.2 vs DeepSeek V4 Pro (Max) head-to-head charts

GLM-5.2 leads 8 and DeepSeek V4 Pro (Max) leads 0 of 8 shared benchmarks. DeepSeek V4 Pro (Max) is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.2DeepSeek V4 Pro (Max)

Overall

54.2GLM-5.2

41.0DeepSeek V4 Pro (Max)

RWT

8.5GLM-5.2

7.0DeepSeek V4 Pro (Max)

HLE

54.7GLM-5.2

37.7DeepSeek V4 Pro (Max)

GPQA

91.2GLM-5.2

90.1DeepSeek V4 Pro (Max)

SWE-Pro

62.1GLM-5.2

55.4DeepSeek V4 Pro (Max)

Terminal-Bench

82.7GLM-5.2

67.9DeepSeek V4 Pro (Max)

MCP Atlas

76.8GLM-5.2

73.6DeepSeek V4 Pro (Max)

Tau2

99.1GLM-5.2

96.2DeepSeek V4 Pro (Max)

GLM-5.2

Input$1.40

Output$4.40

Workload$2.28

Context1M

DeepSeek V4 Pro (Max)

Input$0.43

Output$0.87

Workload$0.61

Context1M

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

More GLM-5.2 and DeepSeek V4 Pro (Max) comparisons

Explore how GLM-5.2 and DeepSeek V4 Pro (Max) stack up against other top-ranked LLMs.

Claude Opus 5 vs GLM-5.2 Claude Opus 5 vs DeepSeek V4 Pro (Max)Claude Fable 5 vs GLM-5.2 Claude Fable 5 vs DeepSeek V4 Pro (Max)GPT-5.6 Sol vs GLM-5.2 GPT-5.6 Sol vs DeepSeek V4 Pro (Max)Kimi K3 vs GLM-5.2 Kimi K3 vs DeepSeek V4 Pro (Max)Qwen3.8 Max vs GLM-5.2 Qwen3.8 Max vs DeepSeek V4 Pro (Max)

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.