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Meta Muse Spark 1.1 VS Z.ai (Zhipu AI) GLM-4.5

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

Decision Recommendation

⚖️ Editorial Verdict: In our analysis, Muse Spark 1.1 is the premium intelligence choice, scoring 2.7% higher on coding benchmarks. However, this accuracy premium comes with a cost overhead: GLM-4.5 is 2.0x cheaper to run. If you are building high-volume, simple chatbots or processing massive amounts of text where budget is critical, GLM-4.5 offers excellent cost savings. For agentic reasoning, code refactoring, or complex logical tasks, the accuracy premium of Muse Spark 1.1 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)Winner (+11.3%)
91.16%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$2.00Input: $1.25 | Output: $4.25
Context WindowLarger
1.05M tokens
Model Specs

GLM-4.5

Benchmarks & Scores

Coding (swe-bench-verified)
64.2%

good at editing existing code, cross-file updates, and multi-component systems

Reasoning (gpqa-diamond)
79.9%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)2.0x cheaper
$1.00Input: $0.60 | Output: $2.20
Context Window
131.07k tokens

Frequently Asked Questions about Muse Spark 1.1 vs GLM-4.5 comparison

GLM-4.5 is cheaper than Muse Spark 1.1. GLM-4.5 has a blended cost of $1.00/1M tokens, which is about 2.0x cheaper than Muse Spark 1.1 at $2.00/1M tokens.

For coding tasks, Muse Spark 1.1 scores 61.5% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases), while GLM-4.5 scores 64.2% on swe-bench-verified (good at editing existing code, cross-file updates, and multi-component systems).