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-6 Luna vs Qwen3.8 27B: benchmark scores, pricing & comparison.
Side-by-side GPT-6 Luna vs Qwen3.8 27B 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-6 Luna ranks higher (#41 vs #42) and wins 5 of 6 shared benchmarks; GPT-6 Luna costs less ($0.10/$0.50 vs $0.45/$3.20 per 1M tokens).
Rank #41 vs #42AskClash overall scores 51.0 vs 50.5.
Pricing $0.10/$0.50 vs $0.45/$3.20Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs Alibaba.
GPT-6 Luna vs Qwen3.8 27B benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | GPT-6 Luna | Qwen3.8 27B |
|---|---|---|
| Overall Score | 51.0 | 50.5 |
| Leaderboard Rank | #41 | #42 |
| ACB | 50.2 | 56.4 |
| Coding Agent Index | 68.1 | — |
| HLE | 38.5 | 30.8 |
| GPQA | — | 89.2 |
| IFEval | — | 79.5 |
| SWE-Pro | — | 61.7 |
| SWE-Atlas | 69.6 | — |
| DeepSWE | 66.6 | 42.2 |
| GDPval-AA | 1431.9 | 1419.9 |
| OSWorld | — | 84.3 |
| Finance Agent | 49.9 | 48.6 |
| CharXiv | — | 90.2 |
| MMMU-Pro | 79.7 | 76.3 |
| ARC-AGI 2 | 59.3 | — |
| Input Price (per 1M tokens) | $0.10 | $0.45 |
| Output Price (per 1M tokens) | $0.50 | $3.20 |
| Context Window | 1.05M | 262K |
| Benchmarks Published | 12 | 12 |
GPT-6 Luna vs Qwen3.8 27B head-to-head charts
GPT-6 Luna leads 6 and Qwen3.8 27B leads 1 of 7 shared benchmarks. GPT-6 Luna is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.
GPT-6 LunaQwen3.8 27B
Overall
ACB
HLE
DeepSWE
GDPval-AA
Finance Agent
MMMU-Pro
GPT-6 Luna
Input$0.10
Output$0.50
Workload$0.20
Context1.05M
Qwen3.8 27B
Input$0.45
Output$3.20
Workload$1.09
Context262K
Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.
More GPT-6 Luna and Qwen3.8 27B comparisons
Explore how GPT-6 Luna and Qwen3.8 27B 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.