LLM Comparison

GPT-6 Astra vs GPT-5.6 Luna: benchmark scores, pricing & comparison.

Side-by-side GPT-6 Astra 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.

Rank #7 vs #22AskClash overall scores 64.9 vs 54.8.
Pricing $10.0/$50.0 vs $1.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs OpenAI.

GPT-6 Astra 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.

MetricGPT-6 AstraGPT-5.6 Luna
Overall Score64.954.8
Leaderboard Rank#7#22
ACB56.1
RWT9.59.5
Coding Agent Index67.075.0
HLE57.2
GPQA96.092.3
SWE-Pro62.7
SWE-Atlas81.0
Terminal-Bench84.7
DeepSWE74.167.2
GDPval-AA1592.0
Finance Agent55.0
MMMU-Pro78.4
ARC-AGI 295.059.5
MRCR100.041.3
Input Price (per 1M tokens)$10.0$1.00
Output Price (per 1M tokens)$50.0$6.00
Context Window1M1M
Benchmarks Published713

GPT-6 Astra vs GPT-5.6 Luna head-to-head charts

GPT-6 Astra leads 5 and GPT-5.6 Luna leads 1 of 7 shared benchmarks. GPT-5.6 Luna is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-6 AstraGPT-5.6 Luna
Overall
64.9GPT-6 Astra
54.8GPT-5.6 Luna
RWT
9.5GPT-6 Astra
9.5GPT-5.6 Luna
Coding Agent Index
67.0GPT-6 Astra
75.0GPT-5.6 Luna
GPQA
96.0GPT-6 Astra
92.3GPT-5.6 Luna
DeepSWE
74.1GPT-6 Astra
67.2GPT-5.6 Luna
ARC-AGI 2
95.0GPT-6 Astra
59.5GPT-5.6 Luna
MRCR
100.0GPT-6 Astra
41.3GPT-5.6 Luna
GPT-6 Astra
Input$10.0
Output$50.0
Workload$20
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-6 Astra and GPT-5.6 Luna comparisons

Explore how GPT-6 Astra and GPT-5.6 Luna stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

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.