Which is better: Qwen3.8 27B or GLM-5.2?

Verdict: Qwen3.8 27B ranks higher (#104 vs #106); GLM-5.2 wins 5 of 7 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $1.40/$4.40 per 1M tokens). AskClash compares Qwen3.8 27B 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 Qwen3.8 27B 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 Qwen3.8 27B and GLM-5.2 when publicly disclosed.

LLM Comparison

Qwen3.8 27B vs GLM-5.2: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 27B 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.

Verdict: Qwen3.8 27B ranks higher (#104 vs #106); GLM-5.2 wins 5 of 7 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $1.40/$4.40 per 1M tokens).

Open live leaderboard Qwen3.8 27B model page GLM-5.2 model page

Rank #104 vs #106AskClash overall scores 48.6 vs 47.7.

Pricing $0.45/$3.20 vs $1.40/$4.40Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightAlibaba vs Z.AI.

Qwen3.8 27B 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	Qwen3.8 27B	GLM-5.2
Overall Score	48.6	47.7
Leaderboard Rank	#104	#106
ACB	56.4	—
RWT	—	8.5
Coding Agent Index	—	74.4
HLE	30.8	54.7
GPQA	89.2	91.2
IFEval	79.5	73.3
SWE-Pro	61.7	62.1
SWE-Atlas	—	74.4
DeepSWE	42.2	43.8
GDPval-AA	1416.9	1372.0
OSWorld	84.3	—
MCP Atlas	—	76.8
Finance Agent	48.6	49.7
CharXiv	90.2	—
MMMU-Pro	76.3	—
ARC-AGI 2	—	22.8
Tau2	—	99.1
Input Price (per 1M tokens)	$0.45	$1.40
Output Price (per 1M tokens)	$3.20	$4.40
Context Window	262K	1M
Benchmarks Published	12	13

Qwen3.8 27B vs GLM-5.2 head-to-head charts

Qwen3.8 27B leads 3 and GLM-5.2 leads 5 of 8 shared benchmarks. Qwen3.8 27B is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 27BGLM-5.2

Overall

48.6Qwen3.8 27B

47.7GLM-5.2

HLE

30.8Qwen3.8 27B

54.7GLM-5.2

GPQA

89.2Qwen3.8 27B

91.2GLM-5.2

IFEval

79.5Qwen3.8 27B

73.3GLM-5.2

SWE-Pro

61.7Qwen3.8 27B

62.1GLM-5.2

DeepSWE

42.2Qwen3.8 27B

43.8GLM-5.2

GDPval-AA

1416.9Qwen3.8 27B

1372.0GLM-5.2

Finance Agent

48.6Qwen3.8 27B

49.7GLM-5.2

Qwen3.8 27B

Input$0.45

Output$3.20

Workload$1.09

Context262K

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 Qwen3.8 27B and GLM-5.2 comparisons

Explore how Qwen3.8 27B and GLM-5.2 stack up against other top-ranked LLMs.

Claude Opus 5.5 vs Qwen3.8 27B Claude Opus 5.5 vs GLM-5.2 Claude Fable 5.1 vs Qwen3.8 27B Claude Fable 5.1 vs GLM-5.2 Claude Sonnet 5.5 vs Qwen3.8 27B Claude Sonnet 5.5 vs GLM-5.2 Claude Opus 5 vs Qwen3.8 27B Claude Opus 5 vs GLM-5.2 Claude Fable 5 vs Qwen3.8 27B Claude Fable 5 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.