LLM Comparison

GPT-5.5 vs Qwen3.8 Max 0902: benchmark scores, pricing & comparison.

Side-by-side GPT-5.5 vs Qwen3.8 Max 0902 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 #11 vs #27AskClash overall scores 62.4 vs 39.0.
Pricing $5.00/$30.0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Alibaba.

GPT-5.5 vs Qwen3.8 Max 0902 benchmark comparison

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

MetricGPT-5.5Qwen3.8 Max 0902
Overall Score62.439.0
Leaderboard Rank#11#27
ACB62.0
RWT8.0
Coding Agent Index61.0
HLE52.243.6
GPQA93.692.6
IFEval82.8
SWE-Pro58.667.7
SWE-Atlas66.3
Terminal-Bench82.786.6
DeepSWE67.069.3
OSWorld78.786.1
MCP Atlas75.3
Finance Agent51.8
CharXiv88.4
MMMU-Pro81.282.7
ARC-AGI 285.0
Tau298.0
MRCR92.9
Input Price (per 1M tokens)$5.00$2.00
Output Price (per 1M tokens)$30.0$6.00
Context Window1M1M
Benchmarks Published1411

GPT-5.5 vs Qwen3.8 Max 0902 head-to-head charts

GPT-5.5 leads 3 and Qwen3.8 Max 0902 leads 5 of 8 shared benchmarks. Qwen3.8 Max 0902 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.5Qwen3.8 Max 0902
Overall
62.4GPT-5.5
39.0Qwen3.8 Max 0902
HLE
52.2GPT-5.5
43.6Qwen3.8 Max 0902
GPQA
93.6GPT-5.5
92.6Qwen3.8 Max 0902
SWE-Pro
58.6GPT-5.5
67.7Qwen3.8 Max 0902
Terminal-Bench
82.7GPT-5.5
86.6Qwen3.8 Max 0902
DeepSWE
67.0GPT-5.5
69.3Qwen3.8 Max 0902
OSWorld
78.7GPT-5.5
86.1Qwen3.8 Max 0902
MMMU-Pro
81.2GPT-5.5
82.7Qwen3.8 Max 0902
GPT-5.5
Input$5.00
Output$30.0
Workload$11
Context1M
Qwen3.8 Max 0902
Input$2.00
Output$6.00
Workload$3.20
Context1M

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

More GPT-5.5 and Qwen3.8 Max 0902 comparisons

Explore how GPT-5.5 and Qwen3.8 Max 0902 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.