How do GPT-5.5 and Qwen3.8 Max compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GPT-5.5 and Qwen3.8 Max when publicly disclosed.

LLM Comparison

GPT-5.5 vs Qwen3.8 Max: benchmark scores, pricing & comparison.

Q: Which is better: GPT-5.5 or Qwen3.8 Max?

AskClash compares GPT-5.5 and Qwen3.8 Max side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, and context window so you can see which model wins on each benchmark.

Side-by-side GPT-5.5 vs Qwen3.8 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.

Open live leaderboard GPT-5.5 model page Qwen3.8 Max model page

Rank #6 vs #13AskClash overall scores 72.8 vs 64.0.

Pricing $5.00/$30.0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.

Proprietary vs ProprietaryOpenAI vs Alibaba.

GPT-5.5 vs Qwen3.8 Max benchmark comparison

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

Metric	GPT-5.5	Qwen3.8 Max
Overall Score	72.8	64.0
Leaderboard Rank	#6	#13
RWT	8.0	—
Coding Agent Index	61.5	—
HLE	52.2	43.6
GPQA	93.6	92.6
IFEval	—	82.8
SWE-Pro	58.6	67.7
Terminal-Bench	82.7	86.6
DeepSWE	67.0	56.6
OSWorld	78.7	86.1
MCP Atlas	75.3	—
Finance Agent	51.8	—
CharXiv	—	88.4
MMMU-Pro	81.2	82.3
ARC-AGI 2	85.0	—
Tau2	98.0	—
MRCR	—	92.9
Input Price (per 1M tokens)	$5.00	$2.00
Output Price (per 1M tokens)	$30.0	$6.00
Context Window	1M	1M
Benchmarks Published	14	10

GPT-5.5 vs Qwen3.8 Max head-to-head charts

GPT-5.5 leads 4 and Qwen3.8 Max leads 4 of 8 shared benchmarks. Qwen3.8 Max is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.5Qwen3.8 Max

Overall

72.8GPT-5.5

64.0Qwen3.8 Max

HLE

52.2GPT-5.5

43.6Qwen3.8 Max

GPQA

93.6GPT-5.5

92.6Qwen3.8 Max

SWE-Pro

58.6GPT-5.5

67.7Qwen3.8 Max

Terminal-Bench

82.7GPT-5.5

86.6Qwen3.8 Max

DeepSWE

67.0GPT-5.5

56.6Qwen3.8 Max

OSWorld

78.7GPT-5.5

86.1Qwen3.8 Max

MMMU-Pro

81.2GPT-5.5

82.3Qwen3.8 Max

GPT-5.5

Input$5.00

Output$30.0

Workload$11

Context1M

Qwen3.8 Max

Input$2.00

Output$6.00

Workload$3.20

Context1M

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

More GPT-5.5 and Qwen3.8 Max comparisons

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Claude Opus 5 vs GPT-5.5 Claude Opus 5 vs Qwen3.8 Max Claude Fable 5 vs GPT-5.5 Claude Fable 5 vs Qwen3.8 Max GPT-5.6 Sol vs GPT-5.5 GPT-5.6 Sol vs Qwen3.8 Max Kimi K3 vs GPT-5.5 Kimi K3 vs Qwen3.8 Max Claude Opus 4.8 vs GPT-5.5 Claude Opus 4.8 vs Qwen3.8 Max

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.