LLM Comparison

Qwen3.8 Max vs Qwen3.7 Max: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Max 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 #5 vs #23AskClash overall scores 70.9 vs 60.5.
Pricing $2.00/$6.00 vs $2.50/$7.50Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryAlibaba vs Alibaba.

Qwen3.8 Max vs Qwen3.7 Max benchmark comparison

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

MetricQwen3.8 MaxQwen3.7 Max
Overall Score70.960.5
Leaderboard Rank#5#23
ACB69.3
RWT7.5
Coding Agent Index43.3
HLE43.641.4
GPQA92.692.4
IFEval82.894.3
SWE-bench80.4
SWE-Pro67.7
SWE-Atlas66.3
Terminal-Bench86.669.7
DeepSWE69.3
GDPval-AA1689.01546.0
OSWorld86.1
MCP Atlas76.4
Finance Agent50.648.4
CharXiv88.4
MMMU-Pro82.7
Tau294.7
MRCR92.990.4
Input Price (per 1M tokens)$2.00$2.50
Output Price (per 1M tokens)$6.00$7.50
Context Window1M1M
Benchmarks Published1611

Qwen3.8 Max vs Qwen3.7 Max head-to-head charts

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

Qwen3.8 MaxQwen3.7 Max
Overall
70.9Qwen3.8 Max
60.5Qwen3.7 Max
HLE
43.6Qwen3.8 Max
41.4Qwen3.7 Max
GPQA
92.6Qwen3.8 Max
92.4Qwen3.7 Max
IFEval
82.8Qwen3.8 Max
94.3Qwen3.7 Max
Terminal-Bench
86.6Qwen3.8 Max
69.7Qwen3.7 Max
GDPval-AA
1689.0Qwen3.8 Max
1546.0Qwen3.7 Max
Finance Agent
50.6Qwen3.8 Max
48.4Qwen3.7 Max
MRCR
92.9Qwen3.8 Max
90.4Qwen3.7 Max
Qwen3.8 Max
Input$2.00
Output$6.00
Workload$3.20
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 Qwen3.8 Max and Qwen3.7 Max comparisons

Explore how Qwen3.8 Max 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.