Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
GPT-5.5 vs GPT-5.6 Luna: benchmark scores, pricing & comparison.
Side-by-side GPT-5.5 vs GPT-5.6 Luna comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.
Verdict: GPT-5.5 ranks higher (#28 vs #35) and wins 6 of 11 shared benchmarks; GPT-5.6 Luna costs less ($1.00/$6.00 vs $5.00/$30.0 per 1M tokens).
Rank #28 vs #35AskClash overall scores 54.5 vs 52.0.
Pricing $5.00/$30.0 vs $1.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs OpenAI.
GPT-5.5 vs GPT-5.6 Luna benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | GPT-5.5 | GPT-5.6 Luna |
|---|---|---|
| Overall Score | 54.5 | 52.0 |
| Leaderboard Rank | #28 | #35 |
| ACB | 62.0 | 56.1 |
| RWT | 8.0 | 9.5 |
| Coding Agent Index | — | 75.0 |
| HLE | 52.2 | 39.5 |
| GPQA | 93.6 | 92.3 |
| IFEval | 75.9 | — |
| SWE-Pro | 58.6 | 62.7 |
| SWE-Atlas | — | 81.0 |
| Terminal-Bench | 14.7 | 11.6 |
| DeepSWE | 67.0 | 67.2 |
| GDPval-AA | 1353.2 | 1592.0 |
| OSWorld | 78.7 | — |
| MCP Atlas | 75.3 | — |
| Finance Agent | 51.8 | 55.0 |
| MMMU-Pro | 81.2 | 78.4 |
| ARC-AGI 2 | 85.0 | 59.5 |
| Tau2 | 98.0 | — |
| MRCR | — | 41.3 |
| Input Price (per 1M tokens) | $5.00 | $1.00 |
| Output Price (per 1M tokens) | $30.0 | $6.00 |
| Context Window | 1M | 1M |
| Benchmarks Published | 14 | 15 |
GPT-5.5 vs GPT-5.6 Luna head-to-head charts
GPT-5.5 leads 7 and GPT-5.6 Luna leads 5 of 12 shared benchmarks. GPT-5.6 Luna is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.
GPT-5.5GPT-5.6 Luna
Overall
ACB
RWT
HLE
GPQA
SWE-Pro
Terminal-Bench
DeepSWE
GDPval-AA
Finance Agent
MMMU-Pro
ARC-AGI 2
GPT-5.5
Input$5.00
Output$30.0
Workload$11
Context1M
GPT-5.6 Luna
Input$1.00
Output$6.00
Workload$2.20
Context1M
Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.
More GPT-5.5 and GPT-5.6 Luna comparisons
Explore how GPT-5.5 and GPT-5.6 Luna stack up against other top-ranked LLMs.
How to read this comparison
Token pricing
Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.
Coverage matters
Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.
This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.