LLM Comparison

Claude Fable 5 vs Qwen3.6-27B: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5 vs Qwen3.6-27B 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.

Rank #2 vs #34AskClash overall scores 92.5 vs 42.4.
Pricing $10.0/$50.0 vs $0/$0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs Alibaba.

Claude Fable 5 vs Qwen3.6-27B benchmark comparison

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

MetricClaude Fable 5Qwen3.6-27B
Overall Score92.542.4
Leaderboard Rank#2#34
RWT9.0
Coding Agent Index77.2
HLE64.524.0
GPQA94.587.8
IFEval80.3
SWE-bench95.577.2
SWE-Pro80.3
SWE-Atlas83.3
Terminal-Bench88.059.3
DeepSWE69.7
OSWorld85.0
Finance Agent56.3
CharXiv93.578.4
MMMU-Pro92.775.8
Tau289.294.2
Input Price (per 1M tokens)$10.0$0
Output Price (per 1M tokens)$50.0$0
Context Window1M+262K
Benchmarks Published177

Claude Fable 5 vs Qwen3.6-27B head-to-head charts

Claude Fable 5 leads 7 and Qwen3.6-27B leads 1 of 8 shared benchmarks. Qwen3.6-27B is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Fable 5Qwen3.6-27B
Overall
92.5Claude Fable 5
42.4Qwen3.6-27B
HLE
64.5Claude Fable 5
24.0Qwen3.6-27B
GPQA
94.5Claude Fable 5
87.8Qwen3.6-27B
SWE-bench
95.5Claude Fable 5
77.2Qwen3.6-27B
Terminal-Bench
88.0Claude Fable 5
59.3Qwen3.6-27B
CharXiv
93.5Claude Fable 5
78.4Qwen3.6-27B
MMMU-Pro
92.7Claude Fable 5
75.8Qwen3.6-27B
Tau2
89.2Claude Fable 5
94.2Qwen3.6-27B
Claude Fable 5
Input$10.0
Output$50.0
Workload$20
Context1M+
Qwen3.6-27B
Input$0
Output$0
Workload$0.00
Context262K

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

More Claude Fable 5 and Qwen3.6-27B comparisons

Explore how Claude Fable 5 and Qwen3.6-27B stack up against other top-ranked LLMs.

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.