How do GLM-5.2 and MiniMax M2.5 compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, LiveCodeBench, and coding agent index scores for both GLM-5.2 and MiniMax M2.5 when publicly disclosed.

LLM Comparison

GLM-5.2 vs MiniMax M2.5: benchmark scores, pricing & comparison.

Q: Which is better: GLM-5.2 or MiniMax M2.5?

AskClash compares GLM-5.2 and MiniMax M2.5 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 MiniMax M2.5 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 MiniMax M2.5 model page

Rank #4 vs #28AskClash overall scores 84.4 vs 44.2.

Pricing $1.40/$4.40 vs $0.30/$1.20Input and output token prices per 1M tokens when published.

Open Weight vs ProprietaryZ.AI vs MiniMax.

GLM-5.2 vs MiniMax M2.5 benchmark comparison

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

Metric	GLM-5.2	MiniMax M2.5
Overall Score	84.4	44.2
Leaderboard Rank	#4	#28
RWT	9.0	—
Coding Agent Index	74.4	—
HLE	54.7	19.1
GPQA	91.2	84.8
IFEval	—	71.6
SWE-bench	—	80.2
SWE-Pro	62.1	55.4
SWE-Atlas	74.4	—
Terminal-Bench	82.7	—
MCP Atlas	76.8	—
Tau2	99.1	95.3
Input Price (per 1M tokens)	$1.40	$0.30
Output Price (per 1M tokens)	$4.40	$1.20
Context Window	1M	128K
Benchmark Cells	9	7

More GLM-5.2 and MiniMax M2.5 comparisons

Explore how GLM-5.2 and MiniMax M2.5 stack up against other top-ranked LLMs.

Claude Mythos Fable 5 vs GLM-5.2 Claude Mythos Fable 5 vs MiniMax M2.5 Sakana Fugu Ultra vs GLM-5.2 Sakana Fugu Ultra vs MiniMax M2.5 Claude Opus 4.8 vs GLM-5.2 Claude Opus 4.8 vs MiniMax M2.5 GLM-5.2 vs Claude Sonnet 5 Claude Sonnet 5 vs MiniMax M2.5 GLM-5.2 vs GPT-5.5 GPT-5.5 vs MiniMax M2.5

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.