Which is better: Qwen3.8 Max or Qwen3.8 27B?

Verdict: Qwen3.8 Max ranks higher (#16 vs #41) and wins 11 of 12 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $2.00/$6.00 per 1M tokens). AskClash compares Qwen3.8 Max and Qwen3.8 27B 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.

How do Qwen3.8 Max and Qwen3.8 27B 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 Qwen3.8 27B when publicly disclosed.

LLM Comparison

Qwen3.8 Max vs Qwen3.8 27B: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Max vs Qwen3.8 27B 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.

Verdict: Qwen3.8 Max ranks higher (#16 vs #41) and wins 11 of 12 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $2.00/$6.00 per 1M tokens).

Open live leaderboard Qwen3.8 Max model page Qwen3.8 27B model page

Rank #16 vs #41AskClash overall scores 59.3 vs 40.8.

Pricing $2.00/$6.00 vs $0.45/$3.20Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightAlibaba vs Alibaba.

Qwen3.8 Max vs Qwen3.8 27B benchmark comparison

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

Metric	Qwen3.8 Max	Qwen3.8 27B
Overall Score	59.3	40.8
Leaderboard Rank	#16	#41
ACB	69.3	56.4
AA Intelligence Index	40.3	20.1
AutomationBench-AA	56.2	48.2
Coding Agent Index	39.2	—
HLE	43.6	30.8
GPQA	92.6	89.2
IFEval	82.8	79.5
SWE-Pro	67.7	61.7
SWE-Atlas	56.2	—
Terminal-Bench 4.0	38.9	—
DeepSWE	69.3	42.2
GDPval-AA	1674.0	1426.2
OSWorld	86.1	84.3
CharXiv	88.4	90.2
MMMU-Pro	82.7	76.3
MRCR	92.9	—
Input Price (per 1M tokens)	$2.00	$0.45
Output Price (per 1M tokens)	$6.00	$3.20
Context Window	1M	262K
Benchmarks Published	14	11

Qwen3.8 Max vs Qwen3.8 27B head-to-head charts

Qwen3.8 Max leads 11 and Qwen3.8 27B leads 1 of 12 shared benchmarks. Qwen3.8 27B is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 MaxQwen3.8 27B

Overall

59.3Qwen3.8 Max

40.8Qwen3.8 27B

ACB

69.3Qwen3.8 Max

56.4Qwen3.8 27B

AA Intelligence Index

40.3Qwen3.8 Max

20.1Qwen3.8 27B

AutomationBench-AA

56.2Qwen3.8 Max

48.2Qwen3.8 27B

HLE

43.6Qwen3.8 Max

30.8Qwen3.8 27B

GPQA

92.6Qwen3.8 Max

89.2Qwen3.8 27B

IFEval

82.8Qwen3.8 Max

79.5Qwen3.8 27B

SWE-Pro

67.7Qwen3.8 Max

61.7Qwen3.8 27B

DeepSWE

69.3Qwen3.8 Max

42.2Qwen3.8 27B

GDPval-AA

1674.0Qwen3.8 Max

1426.2Qwen3.8 27B

OSWorld

86.1Qwen3.8 Max

84.3Qwen3.8 27B

CharXiv

88.4Qwen3.8 Max

90.2Qwen3.8 27B

Qwen3.8 Max

Input$2.00

Output$6.00

Workload$3.20

Context1M

Qwen3.8 27B

Input$0.45

Output$3.20

Workload$1.09

Context262K

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

More Qwen3.8 Max and Qwen3.8 27B comparisons

Explore how Qwen3.8 Max and Qwen3.8 27B stack up against other top-ranked LLMs.

Claude Fable 5.2 vs Qwen3.8 Max Claude Fable 5.2 vs Qwen3.8 27B Claude Opus 5.5 vs Qwen3.8 Max Claude Opus 5.5 vs Qwen3.8 27B Claude Sonnet 5.5 vs Qwen3.8 Max Claude Sonnet 5.5 vs Qwen3.8 27B Claude Fable 5.1 vs Qwen3.8 Max Claude Fable 5.1 vs Qwen3.8 27B Gemini 4 Carbon vs Qwen3.8 Max Gemini 4 Carbon vs Qwen3.8 27B

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.