whichllmmodel
Back to Dashboard

Meta Muse Spark 1.1 VS OpenAI GPT-5.6 Luna

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

Decision Recommendation

⚖️ Editorial Verdict: In our analysis, GPT-5.6 Luna is the premium intelligence choice, scoring 1.2% 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 GPT-5.6 Luna fully justifies the cost.
Was this recommendation helpful?
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

GPT-5.6 Luna

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+1.2%)
62.7%

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

Reasoning (gpqa-diamond)Winner (+1.1%)
92.3%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$2.25Input: $1.00 | Output: $6.00
Context WindowLarger
1.05M tokens

Frequently Asked Questions about Muse Spark 1.1 vs GPT-5.6 Luna comparison

Muse Spark 1.1 is cheaper than GPT-5.6 Luna. Muse Spark 1.1 has a blended cost of $2.00/1M tokens, which is about 1.1x cheaper than GPT-5.6 Luna at $2.25/1M tokens.

GPT-5.6 Luna is better for coding tasks on this benchmark. It scores 62.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Muse Spark 1.1 which scores 61.5%.