LLM Comparison

Hy4 Preview vs GPT-5.6 Luna: benchmark scores, pricing & comparison.

Side-by-side Hy4 Preview 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 #16 vs #22AskClash overall scores 59.9 vs 54.8.
Pricing $0.83/$2.50 vs $1.00/$6.00Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryTencent vs OpenAI.

Hy4 Preview 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.

MetricHy4 PreviewGPT-5.6 Luna
Overall Score59.954.8
Leaderboard Rank#16#22
ACB56.1
RWT8.59.5
Coding Agent Index75.0
HLE43.4
GPQA92.392.3
SWE-Pro65.762.7
SWE-Atlas81.0
Terminal-Bench85.484.7
DeepSWE64.367.2
GDPval-AA1678.01592.0
MCP Atlas83.7
Finance Agent55.0
MMMU-Pro78.4
ARC-AGI 259.5
MRCR41.3
Input Price (per 1M tokens)$0.83$1.00
Output Price (per 1M tokens)$2.50$6.00
Context Window1M1M
Benchmarks Published713

Hy4 Preview vs GPT-5.6 Luna head-to-head charts

Hy4 Preview leads 4 and GPT-5.6 Luna leads 2 of 7 shared benchmarks. Hy4 Preview is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Hy4 PreviewGPT-5.6 Luna
Overall
59.9Hy4 Preview
54.8GPT-5.6 Luna
RWT
8.5Hy4 Preview
9.5GPT-5.6 Luna
GPQA
92.3Hy4 Preview
92.3GPT-5.6 Luna
SWE-Pro
65.7Hy4 Preview
62.7GPT-5.6 Luna
Terminal-Bench
85.4Hy4 Preview
84.7GPT-5.6 Luna
DeepSWE
64.3Hy4 Preview
67.2GPT-5.6 Luna
GDPval-AA
1678.0Hy4 Preview
1592.0GPT-5.6 Luna
Hy4 Preview
Input$0.83
Output$2.50
Workload$1.33
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 Hy4 Preview and GPT-5.6 Luna comparisons

Explore how Hy4 Preview 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.