LLM Comparison

GPT-5.6 Sol vs Qwen3.7 Max: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol 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 #2 vs #11AskClash overall scores 85.6 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-5.6 Sol 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-5.6 SolQwen3.7 Max
Overall Score85.670.7
Leaderboard Rank#2#11
RWT9.57.5
Coding Agent Index80.0
HLE47.241.4
GPQA94.192.4
IFEval94.3
SWE-bench80.4
SWE-Pro64.6
SWE-Atlas84.0
Terminal-Bench88.869.7
DeepSWE72.7
MCP Atlas76.4
Finance Agent53.848.4
MMMU-Pro83.0
ARC-AGI 292.5
Tau285.194.7
MRCR91.590.4
Input Price (per 1M tokens)$5.00$2.50
Output Price (per 1M tokens)$30.0$7.50
Context Window1M1M
Benchmarks Published1411

GPT-5.6 Sol vs Qwen3.7 Max head-to-head charts

GPT-5.6 Sol 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-5.6 SolQwen3.7 Max
Overall
85.6GPT-5.6 Sol
70.7Qwen3.7 Max
RWT
9.5GPT-5.6 Sol
7.5Qwen3.7 Max
HLE
47.2GPT-5.6 Sol
41.4Qwen3.7 Max
GPQA
94.1GPT-5.6 Sol
92.4Qwen3.7 Max
Terminal-Bench
88.8GPT-5.6 Sol
69.7Qwen3.7 Max
Finance Agent
53.8GPT-5.6 Sol
48.4Qwen3.7 Max
Tau2
85.1GPT-5.6 Sol
94.7Qwen3.7 Max
MRCR
91.5GPT-5.6 Sol
90.4Qwen3.7 Max
GPT-5.6 Sol
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-5.6 Sol and Qwen3.7 Max comparisons

Explore how GPT-5.6 Sol 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.