LLM Comparison

Qwen3.8 Max vs DeepSeek V4 Pro (Max): benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Max vs DeepSeek V4 Pro (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 #13 vs #30AskClash overall scores 64.0 vs 41.0.
Pricing $2.00/$6.00 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAlibaba vs DeepSeek.

Qwen3.8 Max vs DeepSeek V4 Pro (Max) benchmark comparison

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

MetricQwen3.8 MaxDeepSeek V4 Pro (Max)
Overall Score64.041.0
Leaderboard Rank#13#30
RWT7.0
HLE43.637.7
GPQA92.690.1
MATH-50064.5
IFEval82.8
SWE-bench80.6
SWE-Pro67.755.4
Terminal-Bench86.667.9
DeepSWE56.6
OSWorld86.1
MCP Atlas73.6
CharXiv88.4
MMMU-Pro82.3
Tau296.2
MRCR92.983.5
Input Price (per 1M tokens)$2.00$0.43
Output Price (per 1M tokens)$6.00$0.87
Context Window1M1M
Benchmarks Published109

Qwen3.8 Max vs DeepSeek V4 Pro (Max) head-to-head charts

Qwen3.8 Max leads 6 and DeepSeek V4 Pro (Max) leads 0 of 6 shared benchmarks. DeepSeek V4 Pro (Max) is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 MaxDeepSeek V4 Pro (Max)
Overall
64.0Qwen3.8 Max
41.0DeepSeek V4 Pro (Max)
HLE
43.6Qwen3.8 Max
37.7DeepSeek V4 Pro (Max)
GPQA
92.6Qwen3.8 Max
90.1DeepSeek V4 Pro (Max)
SWE-Pro
67.7Qwen3.8 Max
55.4DeepSeek V4 Pro (Max)
Terminal-Bench
86.6Qwen3.8 Max
67.9DeepSeek V4 Pro (Max)
MRCR
92.9Qwen3.8 Max
83.5DeepSeek V4 Pro (Max)
Qwen3.8 Max
Input$2.00
Output$6.00
Workload$3.20
Context1M
DeepSeek V4 Pro (Max)
Input$0.43
Output$0.87
Workload$0.61
Context1M

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

More Qwen3.8 Max and DeepSeek V4 Pro (Max) comparisons

Explore how Qwen3.8 Max and DeepSeek V4 Pro (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.