How do Qwen3.8 Max and Qwen3.6 Plus compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both Qwen3.8 Max and Qwen3.6 Plus when publicly disclosed.

LLM Comparison

Qwen3.8 Max vs Qwen3.6 Plus: benchmark scores, pricing & comparison.

Q: Which is better: Qwen3.8 Max or Qwen3.6 Plus?

AskClash compares Qwen3.8 Max and Qwen3.6 Plus side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

Side-by-side Qwen3.8 Max vs Qwen3.6 Plus 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.

Open live leaderboard Qwen3.8 Max model page Qwen3.6 Plus model page

Rank #7 vs #32AskClash overall scores 74.4 vs 42.8.

Pricing $2.00/$6.00 vs $0.50/$3.00Input and output token prices per 1M tokens when published.

Open Weight vs ProprietaryAlibaba vs Alibaba.

Qwen3.8 Max vs Qwen3.6 Plus benchmark comparison

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

Metric	Qwen3.8 Max	Qwen3.6 Plus
Overall Score	74.4	42.8
Leaderboard Rank	#7	#32
ACB	59.0	—
HLE	43.6	28.8
GPQA	92.6	90.4
IFEval	82.8	94.3
SWE-bench	—	78.8
SWE-Pro	67.7	—
Terminal-Bench	86.6	—
DeepSWE	56.6	—
OSWorld	86.1	—
MCP Atlas	—	48.2
Finance Agent	50.6	40.8
CharXiv	88.4	81.5
MMMU-Pro	82.3	78.8
Tau2	—	97.7
MRCR	92.9	—
Input Price (per 1M tokens)	$2.00	$0.50
Output Price (per 1M tokens)	$6.00	$3.00
Context Window	1M	1M
Benchmarks Published	12	10

Qwen3.8 Max vs Qwen3.6 Plus head-to-head charts

Qwen3.8 Max leads 6 and Qwen3.6 Plus leads 1 of 7 shared benchmarks. Qwen3.6 Plus is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 MaxQwen3.6 Plus

Overall

74.4Qwen3.8 Max

42.8Qwen3.6 Plus

HLE

43.6Qwen3.8 Max

28.8Qwen3.6 Plus

GPQA

92.6Qwen3.8 Max

90.4Qwen3.6 Plus

IFEval

82.8Qwen3.8 Max

94.3Qwen3.6 Plus

Finance Agent

50.6Qwen3.8 Max

40.8Qwen3.6 Plus

CharXiv

88.4Qwen3.8 Max

81.5Qwen3.6 Plus

MMMU-Pro

82.3Qwen3.8 Max

78.8Qwen3.6 Plus

Qwen3.8 Max

Input$2.00

Output$6.00

Workload$3.20

Context1M

Qwen3.6 Plus

Input$0.50

Output$3.00

Workload$1.10

Context1M

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

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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.