Meta Muse Spark 1.1 VS Z.ai (Zhipu AI) GLM-4.7
Decision Recommendation
⚖️ Editorial Verdict: In our analysis, GLM-4.7 is the premium intelligence choice, scoring 12.3% higher on coding benchmarks. It also maintains strong cost efficiency. 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-4.7 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 (+5.5%)
91.16%graduate-level science QA
Cost & Performance
Cost (per 1M tokens)
$2.00Input: $1.25 | Output: $4.25Context WindowLarger
1.05M tokensModel Specs
GLM-4.7
Benchmarks & Scores
Coding (swe-bench-verified)
73.8%good at editing existing code, cross-file updates, and multi-component systems
Reasoning (gpqa-diamond)
85.7%graduate-level science QA
Cost & Performance
Cost (per 1M tokens)2.0x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
204.8k tokensFrequently Asked Questions about Muse Spark 1.1 vs GLM-4.7 comparison
GLM-4.7 is cheaper than Muse Spark 1.1. GLM-4.7 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-4.7 scores 73.8% on swe-bench-verified (good at editing existing code, cross-file updates, and multi-component systems).
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