LLM Comparison

GPT-5.5 vs Qwen3.7 Max: benchmark scores, pricing & comparison.

Side-by-side GPT-5.5 vs Qwen3.7 Max 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 #10 vs #12AskClash overall scores 75.5 vs 70.7.
Pricing $5.00/$30.0 vs $2.50/$7.50Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Alibaba.

GPT-5.5 vs Qwen3.7 Max benchmark comparison

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

MetricGPT-5.5Qwen3.7 Max
Overall Score75.570.7
Leaderboard Rank#10#12
RWT8.07.5
Coding Agent Index56.6
HLE52.241.4
GPQA93.692.4
IFEval94.3
SWE-bench80.4
SWE-Pro58.6
Terminal-Bench82.769.7
DeepSWE67.0
OSWorld78.7
MCP Atlas75.376.4
Finance Agent51.848.4
MMMU-Pro81.2
ARC-AGI 285.0
Tau298.094.7
MRCR90.4
Input Price (per 1M tokens)$5.00$2.50
Output Price (per 1M tokens)$30.0$7.50
Context Window1M1M
Benchmarks Published1311

GPT-5.5 vs Qwen3.7 Max head-to-head charts

GPT-5.5 leads 7 and Qwen3.7 Max leads 1 of 8 shared benchmarks. Qwen3.7 Max is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.5Qwen3.7 Max
Overall
75.5GPT-5.5
70.7Qwen3.7 Max
RWT
8.0GPT-5.5
7.5Qwen3.7 Max
HLE
52.2GPT-5.5
41.4Qwen3.7 Max
GPQA
93.6GPT-5.5
92.4Qwen3.7 Max
Terminal-Bench
82.7GPT-5.5
69.7Qwen3.7 Max
MCP Atlas
75.3GPT-5.5
76.4Qwen3.7 Max
Finance Agent
51.8GPT-5.5
48.4Qwen3.7 Max
Tau2
98.0GPT-5.5
94.7Qwen3.7 Max
GPT-5.5
Input$5.00
Output$30.0
Workload$11
Context1M
Qwen3.7 Max
Input$2.50
Output$7.50
Workload$4.00
Context1M

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

More GPT-5.5 and Qwen3.7 Max comparisons

Explore how GPT-5.5 and Qwen3.7 Max 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.