LLM Comparison

GPT-5.6 Luna vs Gemini 3.5 Flash-Lite: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Luna vs Gemini 3.5 Flash-Lite 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 #13 vs #61AskClash overall scores 68.9 vs 14.2.
Pricing $1.00/$6.00 vs $0.30/$2.50Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Google.

GPT-5.6 Luna vs Gemini 3.5 Flash-Lite benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricGPT-5.6 LunaGemini 3.5 Flash-Lite
Overall Score68.914.2
Leaderboard Rank#13#61
RWT9.57.0
Coding Agent Index75.0
GPQA92.3
SWE-Pro62.754.2
SWE-Atlas81.0
Terminal-Bench84.754.0
DeepSWE67.2
OSWorld74.0
Finance Agent55.0
MMMU-Pro78.4
ARC-AGI 259.5
MRCR41.372.2
Input Price (per 1M tokens)$1.00$0.30
Output Price (per 1M tokens)$6.00$2.50
Context Window1M1M
Benchmarks Published126

GPT-5.6 Luna vs Gemini 3.5 Flash-Lite head-to-head charts

GPT-5.6 Luna leads 4 and Gemini 3.5 Flash-Lite leads 1 of 5 shared benchmarks. Gemini 3.5 Flash-Lite is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 LunaGemini 3.5 Flash-Lite
Overall
68.9GPT-5.6 Luna
14.2Gemini 3.5 Flash-Lite
RWT
9.5GPT-5.6 Luna
7.0Gemini 3.5 Flash-Lite
SWE-Pro
62.7GPT-5.6 Luna
54.2Gemini 3.5 Flash-Lite
Terminal-Bench
84.7GPT-5.6 Luna
54.0Gemini 3.5 Flash-Lite
MRCR
41.3GPT-5.6 Luna
72.2Gemini 3.5 Flash-Lite
GPT-5.6 Luna
Input$1.00
Output$6.00
Workload$2.20
Context1M
Gemini 3.5 Flash-Lite
Input$0.30
Output$2.50
Workload$0.80
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More GPT-5.6 Luna and Gemini 3.5 Flash-Lite comparisons

Explore how GPT-5.6 Luna and Gemini 3.5 Flash-Lite 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.