LLM Comparison

Qwen3.8 Max vs Claude Sonnet 5: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Max vs Claude Sonnet 5 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 #10AskClash overall scores 75.8 vs 71.6.
Pricing $2.00/$6.00 vs $3.00/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAlibaba vs Anthropic.

Qwen3.8 Max vs Claude Sonnet 5 benchmark comparison

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

MetricQwen3.8 MaxClaude Sonnet 5
Overall Score75.871.6
Leaderboard Rank#5#10
RWT8.5
HLE43.657.4
GPQA92.691.1
IFEval82.8
SWE-bench85.2
SWE-Pro67.763.2
Terminal-Bench86.680.4
DeepSWE56.653.8
OSWorld86.181.2
CharXiv88.488.3
MMMU-Pro82.377.3
MRCR92.9
Input Price (per 1M tokens)$2.00$3.00
Output Price (per 1M tokens)$6.00$15.0
Context Window1M1M
Benchmarks Published1112

Qwen3.8 Max vs Claude Sonnet 5 head-to-head charts

Qwen3.8 Max leads 8 and Claude Sonnet 5 leads 1 of 9 shared benchmarks. Qwen3.8 Max is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 MaxClaude Sonnet 5
Overall
75.8Qwen3.8 Max
71.6Claude Sonnet 5
HLE
43.6Qwen3.8 Max
57.4Claude Sonnet 5
GPQA
92.6Qwen3.8 Max
91.1Claude Sonnet 5
SWE-Pro
67.7Qwen3.8 Max
63.2Claude Sonnet 5
Terminal-Bench
86.6Qwen3.8 Max
80.4Claude Sonnet 5
DeepSWE
56.6Qwen3.8 Max
53.8Claude Sonnet 5
OSWorld
86.1Qwen3.8 Max
81.2Claude Sonnet 5
CharXiv
88.4Qwen3.8 Max
88.3Claude Sonnet 5
MMMU-Pro
82.3Qwen3.8 Max
77.3Claude Sonnet 5
Qwen3.8 Max
Input$2.00
Output$6.00
Workload$3.20
Context1M
Claude Sonnet 5
Input$3.00
Output$15.0
Workload$6.00
Context1M

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

More Qwen3.8 Max and Claude Sonnet 5 comparisons

Explore how Qwen3.8 Max and Claude Sonnet 5 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.