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.

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

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.

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.

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

Rank #6 vs #17AskClash overall scores 74.4 vs 57.0.

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	74.4	57.0
Leaderboard Rank	#6	#17
ACB	59.0	56.4
HLE	43.6	30.8
GPQA	92.6	89.2
IFEval	82.8	79.5
SWE-Pro	67.7	61.7
Terminal-Bench	86.6	73.0
DeepSWE	56.6	42.2
OSWorld	86.1	84.3
Finance Agent	50.6	—
CharXiv	88.4	90.2
MMMU-Pro	82.3	—
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	12	9

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

Qwen3.8 Max leads 9 and Qwen3.8 27B leads 1 of 10 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

74.4Qwen3.8 Max

57.0Qwen3.8 27B

ACB

59.0Qwen3.8 Max

56.4Qwen3.8 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

Terminal-Bench

86.6Qwen3.8 Max

73.0Qwen3.8 27B

DeepSWE

56.6Qwen3.8 Max

42.2Qwen3.8 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.

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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.