Which is better: Muse Wonder or Qwen3.8 27B?

Verdict: Muse Wonder ranks higher (#11 vs #40) and wins 5 of 5 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $4.00/$20.0 per 1M tokens). AskClash compares Muse Wonder 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 Muse Wonder 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 Muse Wonder and Qwen3.8 27B when publicly disclosed.

LLM Comparison

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

Side-by-side Muse Wonder 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: Muse Wonder ranks higher (#11 vs #40) and wins 5 of 5 shared benchmarks; Qwen3.8 27B costs less ($0.45/$3.20 vs $4.00/$20.0 per 1M tokens).

Open live leaderboard Muse Wonder model page Qwen3.8 27B model page

Rank #11 vs #40AskClash overall scores 64.7 vs 50.4.

Pricing $4.00/$20.0 vs $0.45/$3.20Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightMeta vs Alibaba.

Muse Wonder 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	Muse Wonder	Qwen3.8 27B
Overall Score	64.7	50.4
Leaderboard Rank	#11	#40
ACB	62.3	56.4
HLE	50.1	30.8
GPQA	—	89.2
IFEval	—	79.5
SWE-Pro	—	61.7
Terminal-Bench	52.0	—
DeepSWE	78.8	42.2
GDPval-AA	1770.3	1419.1
OSWorld	—	84.3
Finance Agent	56.6	48.6
CharXiv	—	90.2
MMMU-Pro	—	76.3
Input Price (per 1M tokens)	$4.00	$0.45
Output Price (per 1M tokens)	$20.0	$3.20
Context Window	1M	262K
Benchmarks Published	9	12

Muse Wonder vs Qwen3.8 27B head-to-head charts

Muse Wonder leads 6 and Qwen3.8 27B leads 0 of 6 shared benchmarks. Qwen3.8 27B is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Muse WonderQwen3.8 27B

Overall

64.7Muse Wonder

50.4Qwen3.8 27B

ACB

62.3Muse Wonder

56.4Qwen3.8 27B

HLE

50.1Muse Wonder

30.8Qwen3.8 27B

DeepSWE

78.8Muse Wonder

42.2Qwen3.8 27B

GDPval-AA

1770.3Muse Wonder

1419.1Qwen3.8 27B

Finance Agent

56.6Muse Wonder

48.6Qwen3.8 27B

Muse Wonder

Input$4.00

Output$20.0

Workload$8.00

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 Muse Wonder and Qwen3.8 27B comparisons

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

Claude Opus 5.5 vs Muse Wonder Claude Opus 5.5 vs Qwen3.8 27B Claude Fable 5.1 vs Muse Wonder Claude Fable 5.1 vs Qwen3.8 27B Claude Sonnet 5.5 vs Muse Wonder Claude Sonnet 5.5 vs Qwen3.8 27B Claude Opus 5 vs Muse Wonder Claude Opus 5 vs Qwen3.8 27B Claude Fable 5 vs Muse Wonder Claude Fable 5 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.