How do DeepSeek V4 Pro 0813 and GLM-5.2 compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both DeepSeek V4 Pro 0813 and GLM-5.2 when publicly disclosed.

LLM Comparison

DeepSeek V4 Pro 0813 vs GLM-5.2: benchmark scores, pricing & comparison.

Q: Which is better: DeepSeek V4 Pro 0813 or GLM-5.2?

AskClash compares DeepSeek V4 Pro 0813 and GLM-5.2 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 DeepSeek V4 Pro 0813 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.

Open live leaderboard DeepSeek V4 Pro 0813 model page GLM-5.2 model page

Rank #17 vs #21AskClash overall scores 60.5 vs 53.3.

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

Open Weight vs Open WeightDeepSeek vs Z.AI.

DeepSeek V4 Pro 0813 vs GLM-5.2 benchmark comparison

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

Metric	DeepSeek V4 Pro 0813	GLM-5.2
Overall Score	60.5	53.3
Leaderboard Rank	#17	#21
RWT	7.0	8.5
Coding Agent Index	—	74.4
HLE	42.7	54.7
GPQA	90.1	91.2
IFEval	—	73.3
SWE-bench	80.6	—
SWE-Pro	55.4	62.1
SWE-Atlas	—	74.4
Terminal-Bench	87.9	82.7
DeepSWE	62.7	43.8
MCP Atlas	73.6	76.8
Tau2	—	99.1
Input Price (per 1M tokens)	$0.43	$1.40
Output Price (per 1M tokens)	$0.87	$4.40
Context Window	1M	1M
Benchmarks Published	9	11

DeepSeek V4 Pro 0813 vs GLM-5.2 head-to-head charts

DeepSeek V4 Pro 0813 leads 3 and GLM-5.2 leads 5 of 8 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

DeepSeek V4 Pro 0813GLM-5.2

Overall

60.5DeepSeek V4 Pro 0813

53.3GLM-5.2

RWT

7.0DeepSeek V4 Pro 0813

8.5GLM-5.2

HLE

42.7DeepSeek V4 Pro 0813

54.7GLM-5.2

GPQA

90.1DeepSeek V4 Pro 0813

91.2GLM-5.2

SWE-Pro

55.4DeepSeek V4 Pro 0813

62.1GLM-5.2

Terminal-Bench

87.9DeepSeek V4 Pro 0813

82.7GLM-5.2

DeepSWE

62.7DeepSeek V4 Pro 0813

43.8GLM-5.2

MCP Atlas

73.6DeepSeek V4 Pro 0813

76.8GLM-5.2

DeepSeek V4 Pro 0813

Input$0.43

Output$0.87

Workload$0.61

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 DeepSeek V4 Pro 0813 and GLM-5.2 comparisons

Explore how DeepSeek V4 Pro 0813 and GLM-5.2 stack up against other top-ranked LLMs.

Claude Opus 5 vs DeepSeek V4 Pro 0813 Claude Opus 5 vs GLM-5.2 Claude Fable 5 vs DeepSeek V4 Pro 0813 Claude Fable 5 vs GLM-5.2 GPT-5.6 Sol vs DeepSeek V4 Pro 0813 GPT-5.6 Sol vs GLM-5.2 Kimi K3 vs DeepSeek V4 Pro 0813 Kimi K3 vs GLM-5.2 Grok 4.6 vs DeepSeek V4 Pro 0813 Grok 4.6 vs GLM-5.2

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.