How do DeepSeek V4 Flash 0731 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 Flash 0731 and GLM-5.2 when publicly disclosed.

LLM Comparison

DeepSeek V4 Flash 0731 vs GLM-5.2: benchmark scores, pricing & comparison.

Q: Which is better: DeepSeek V4 Flash 0731 or GLM-5.2?

AskClash compares DeepSeek V4 Flash 0731 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 Flash 0731 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 Flash 0731 model page GLM-5.2 model page

Rank #16 vs #17AskClash overall scores 56.1 vs 54.8.

Pricing $0.14/$0.28 vs $1.40/$4.40Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightDeepSeek vs Z.AI.

DeepSeek V4 Flash 0731 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 Flash 0731	GLM-5.2
Overall Score	56.1	54.8
Leaderboard Rank	#16	#17
RWT	—	8.5
Coding Agent Index	—	74.4
HLE	37.0	54.7
GPQA	91.0	91.2
MATH-500	57.4	—
IFEval	—	73.3
SWE-bench	79.0	—
SWE-Pro	—	62.1
SWE-Atlas	—	74.4
Terminal-Bench	82.7	82.7
DeepSWE	54.4	43.8
MCP Atlas	69.0	76.8
Tau2	—	99.1
MRCR	78.7	—
Input Price (per 1M tokens)	$0.14	$1.40
Output Price (per 1M tokens)	$0.28	$4.40
Context Window	1M	1M
Benchmarks Published	9	11

DeepSeek V4 Flash 0731 vs GLM-5.2 head-to-head charts

DeepSeek V4 Flash 0731 leads 2 and GLM-5.2 leads 3 of 6 shared benchmarks. DeepSeek V4 Flash 0731 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

DeepSeek V4 Flash 0731GLM-5.2

Overall

56.1DeepSeek V4 Flash 0731

54.8GLM-5.2

HLE

37.0DeepSeek V4 Flash 0731

54.7GLM-5.2

GPQA

91.0DeepSeek V4 Flash 0731

91.2GLM-5.2

Terminal-Bench

82.7DeepSeek V4 Flash 0731

82.7GLM-5.2

DeepSWE

54.4DeepSeek V4 Flash 0731

43.8GLM-5.2

MCP Atlas

69.0DeepSeek V4 Flash 0731

76.8GLM-5.2

DeepSeek V4 Flash 0731

Input$0.14

Output$0.28

Workload$0.20

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 Flash 0731 and GLM-5.2 comparisons

Explore how DeepSeek V4 Flash 0731 and GLM-5.2 stack up against other top-ranked LLMs.

Claude Opus 5 vs DeepSeek V4 Flash 0731 Claude Opus 5 vs GLM-5.2 Claude Fable 5 vs DeepSeek V4 Flash 0731 Claude Fable 5 vs GLM-5.2 GPT-5.6 Sol vs DeepSeek V4 Flash 0731 GPT-5.6 Sol vs GLM-5.2 Kimi K3 vs DeepSeek V4 Flash 0731 Kimi K3 vs GLM-5.2 Claude Opus 4.8 vs DeepSeek V4 Flash 0731 Claude Opus 4.8 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.