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Meta Muse Spark 1.1 VS Z.ai (Zhipu AI) GLM-5.2

✍️ Analysis by:the whichllmmodel Editorial Team|📅 Updated: June 2026

Decision Recommendation

⚖️ Editorial Verdict: In our analysis, GLM-5.2 is the premium intelligence choice, scoring 0.6% higher on coding benchmarks. However, this accuracy premium comes with a cost overhead: Muse Spark 1.1 is 1.1x cheaper to run. If you are building high-volume, simple chatbots or processing massive amounts of text where budget is critical, Muse Spark 1.1 offers excellent cost savings. For agentic reasoning, code refactoring, or complex logical tasks, the accuracy premium of GLM-5.2 fully justifies the cost.
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Model Specs

Muse Spark 1.1

Benchmarks & Scores

Coding (swe-bench-pro)
61.5%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)
91.16%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)1.1x cheaper
$2.00Input: $1.25 | Output: $4.25
Context Window
1.05M tokens
Model Specs

GLM-5.2

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+0.6%)
62.1%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+0.0%)
91.2%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40
Context Window
1.05M tokens

Frequently Asked Questions about Muse Spark 1.1 vs GLM-5.2 comparison

Muse Spark 1.1 is cheaper than GLM-5.2. Muse Spark 1.1 has a blended cost of $2.00/1M tokens, which is about 1.1x cheaper than GLM-5.2 at $2.15/1M tokens.

GLM-5.2 is better for coding tasks on this benchmark. It scores 62.1% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Muse Spark 1.1 which scores 61.5%.