Which is better: SWE-2 or Qwen3.8 Max?

Verdict: SWE-2 ranks higher (#10 vs #11) and wins 6 of 11 shared benchmarks; SWE-2 costs less ($0/$0 vs $2.00/$6.00 per 1M tokens). AskClash compares SWE-2 and Qwen3.8 Max 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 SWE-2 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 SWE-2 and Qwen3.8 Max when publicly disclosed.

LLM Comparison

SWE-2 vs Qwen3.8 Max: benchmark scores, pricing & comparison.

Side-by-side SWE-2 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.

Verdict: SWE-2 ranks higher (#10 vs #11) and wins 6 of 11 shared benchmarks; SWE-2 costs less ($0/$0 vs $2.00/$6.00 per 1M tokens).

Open live leaderboard SWE-2 model page Qwen3.8 Max model page

Rank #10 vs #11AskClash overall scores 68.0 vs 67.9.

Pricing $0/$0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightCognition vs Alibaba.

SWE-2 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	SWE-2	Qwen3.8 Max
Overall Score	68.0	67.9
Leaderboard Rank	#10	#11
ACB	60.0	69.3
RWT	8.5	—
Coding Agent Index	51.9	43.3
HLE	43.5	43.6
GPQA	93.5	92.6
IFEval	—	82.8
SWE-Pro	—	67.7
SWE-Atlas	66.1	66.3
Terminal-Bench	92.8	86.6
DeepSWE	73.0	69.3
GDPval-AA	1668.0	1667.7
OSWorld	—	86.1
MCP Atlas	84.2	—
Finance Agent	54.4	50.6
CharXiv	84.8	88.4
MMMU-Pro	81.6	82.7
MRCR	—	92.9
Input Price (per 1M tokens)	$0	$2.00
Output Price (per 1M tokens)	$0	$6.00
Context Window	256K	1M
Benchmarks Published	13	15

SWE-2 vs Qwen3.8 Max head-to-head charts

SWE-2 leads 7 and Qwen3.8 Max leads 5 of 12 shared benchmarks. SWE-2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

SWE-2Qwen3.8 Max

Overall

68.0SWE-2

67.9Qwen3.8 Max

ACB

60.0SWE-2

69.3Qwen3.8 Max

Coding Agent Index

51.9SWE-2

43.3Qwen3.8 Max

HLE

43.5SWE-2

43.6Qwen3.8 Max

GPQA

93.5SWE-2

92.6Qwen3.8 Max

SWE-Atlas

66.1SWE-2

66.3Qwen3.8 Max

Terminal-Bench

92.8SWE-2

86.6Qwen3.8 Max

DeepSWE

73.0SWE-2

69.3Qwen3.8 Max

GDPval-AA

1668.0SWE-2

1667.7Qwen3.8 Max

Finance Agent

54.4SWE-2

50.6Qwen3.8 Max

CharXiv

84.8SWE-2

88.4Qwen3.8 Max

MMMU-Pro

81.6SWE-2

82.7Qwen3.8 Max

SWE-2

Input$0

Output$0

Workload$0.00

Context256K

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 SWE-2 and Qwen3.8 Max comparisons

Explore how SWE-2 and Qwen3.8 Max stack up against other top-ranked LLMs.

Claude Fable 5.1 vs SWE-2 Claude Fable 5.1 vs Qwen3.8 Max Claude Opus 5.5 vs SWE-2 Claude Opus 5.5 vs Qwen3.8 Max Claude Fable 5 vs SWE-2 Claude Fable 5 vs Qwen3.8 Max Claude Opus 5 vs SWE-2 Claude Opus 5 vs Qwen3.8 Max GPT-5.6 Sol vs SWE-2 GPT-5.6 Sol 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.