Which is better: SWE-2 or GLM-5.2?

AskClash compares SWE-2 and GLM-5.2 side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

How do SWE-2 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 SWE-2 and GLM-5.2 when publicly disclosed.

LLM Comparison

SWE-2 vs GLM-5.2: benchmark scores, pricing & comparison.

Side-by-side SWE-2 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 SWE-2 model page GLM-5.2 model page

Rank #10 vs #22AskClash overall scores 66.3 vs 61.5.

Pricing $0/$0 vs $1.40/$4.40Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightCognition vs Z.AI.

SWE-2 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	SWE-2	GLM-5.2
Overall Score	66.3	61.5
Leaderboard Rank	#10	#22
ACB	60.0	—
RWT	8.5	8.5
Coding Agent Index	51.9	74.4
HLE	43.5	54.7
GPQA	93.5	91.2
IFEval	—	73.3
SWE-Pro	—	62.1
SWE-Atlas	66.1	74.4
Terminal-Bench	92.8	82.7
DeepSWE	73.0	43.8
GDPval-AA	1668.0	1406.1
MCP Atlas	84.2	76.8
Finance Agent	54.4	49.7
CharXiv	84.8	—
MMMU-Pro	81.6	—
Tau2	—	99.1
Input Price (per 1M tokens)	$0	$1.40
Output Price (per 1M tokens)	$0	$4.40
Context Window	256K	1M
Benchmarks Published	13	13

SWE-2 vs GLM-5.2 head-to-head charts

SWE-2 leads 7 and GLM-5.2 leads 3 of 11 shared benchmarks. SWE-2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

SWE-2GLM-5.2

Overall

66.3SWE-2

61.5GLM-5.2

RWT

8.5SWE-2

8.5GLM-5.2

Coding Agent Index

51.9SWE-2

74.4GLM-5.2

HLE

43.5SWE-2

54.7GLM-5.2

GPQA

93.5SWE-2

91.2GLM-5.2

SWE-Atlas

66.1SWE-2

74.4GLM-5.2

Terminal-Bench

92.8SWE-2

82.7GLM-5.2

DeepSWE

73.0SWE-2

43.8GLM-5.2

GDPval-AA

1668.0SWE-2

1406.1GLM-5.2

MCP Atlas

84.2SWE-2

76.8GLM-5.2

Finance Agent

54.4SWE-2

49.7GLM-5.2

SWE-2

Input$0

Output$0

Workload$0.00

Context256K

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 SWE-2 and GLM-5.2 comparisons

Explore how SWE-2 and GLM-5.2 stack up against other top-ranked LLMs.

Claude Fable 5.1 vs SWE-2 Claude Fable 5.1 vs GLM-5.2 Claude Fable 5 vs SWE-2 Claude Fable 5 vs GLM-5.2 Claude Opus 5 vs SWE-2 Claude Opus 5 vs GLM-5.2 GPT-5.6 Sol vs SWE-2 GPT-5.6 Sol vs GLM-5.2 Qwen3.8 Max vs SWE-2 Qwen3.8 Max 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.