GPT-6 Luna vs Perplexity Decider v1.2
A direct, empirical evaluation of GPT-6 Luna (OpenAI) against Perplexity Decider v1.2 (Perplexity AI).
GPT-6 Luna
Developed by OpenAI · Proprietary High-Throughput Distillation parameters
High-throughput document extraction, sub-second routing, customer service triage, code autocomplete, and cost-optimized reasoning via Luna Pro mode.
Perplexity Decider v1.2
Developed by Perplexity AI · 27 Billion Parameters parameters
Sub-50ms intent classification, multimodal screenshot routing, calibrated confidence bounds, and automated API dispatcher pipelines.
| Metric | GPT-6 Luna | Perplexity Decider v1.2 |
|---|---|---|
| SWE-bench Verified | 48.2% | 64.2% |
| MMLU-Pro | 74.6% | 88.4% |
| MATH-500 | 84.1% | 89.1% |
| Context Window | 1,050,000 tokens | 64,000 tokens |
| Input Pricing (per 1M) | $0.10 | $0.20 |
| Output Pricing (per 1M) | $0.50 | $0.60 |
Architectural & Practical Deployment Analysis
Evaluating GPT-6 Luna (OpenAI) alongside Perplexity Decider v1.2 (Perplexity AI) highlights key technical trade-offs across neural parameter scale and compute efficiency. GPT-6 Luna executes across Proprietary High-Throughput Distillation total parameters with Fast Utility & Speculative Decoder active per token, whereas Perplexity Decider v1.2 operates on 27 Billion Parameters parameters with 27.2B Dedicated Multimodal Decision Engine active per token.
On SWE-bench Verified software engineering tasks, GPT-6 Luna achieves 48.2% autonomous resolution rate, compared to 64.2% for Perplexity Decider v1.2. On complex reasoning benchmarks, GPT-6 Luna posts 74.6% on MMLU-Pro and 84.1% on MATH-500, against 88.4% and 89.1% respectively for Perplexity Decider v1.2.
From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $2.20 on GPT-6 Luna versus $3.20 on Perplexity Decider v1.2.
Recommendation: Deploy GPT-6 Luna when your infrastructure prioritizes high-throughput document extraction, sub-second routing, customer service triage, code autocomplete, and cost-optimized reasoning via luna pro mode.. Deploy Perplexity Decider v1.2 when workload requirements favor sub-50ms intent classification, multimodal screenshot routing, calibrated confidence bounds, and automated api dispatcher pipelines..