LLM Comparison

Claude Fable 5.1 vs Qwen3.7 Max: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5.1 vs Qwen3.7 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.

Rank #1 vs #24AskClash overall scores 92.0 vs 48.6.
Pricing $10.0/$50.0 vs $2.50/$7.50Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs Alibaba.

Claude Fable 5.1 vs Qwen3.7 Max benchmark comparison

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

MetricClaude Fable 5.1Qwen3.7 Max
Overall Score92.048.6
Leaderboard Rank#1#24
ACB79.2
RWT9.07.5
HLE65.041.4
GPQA93.792.4
IFEval94.3
SWE-bench80.4
SWE-Pro81.2
Terminal-Bench91.469.7
DeepSWE67.4
GDPval-AA1853.01546.0
MCP Atlas76.4
Finance Agent58.948.4
MMMU-Pro90.6
ARC-AGI 290.0
Tau294.7
MRCR90.4
Input Price (per 1M tokens)$10.0$2.50
Output Price (per 1M tokens)$50.0$7.50
Context Window1M1M
Benchmarks Published1111

Claude Fable 5.1 vs Qwen3.7 Max head-to-head charts

Claude Fable 5.1 leads 7 and Qwen3.7 Max leads 0 of 7 shared benchmarks. Qwen3.7 Max is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Fable 5.1Qwen3.7 Max
Overall
92.0Claude Fable 5.1
48.6Qwen3.7 Max
RWT
9.0Claude Fable 5.1
7.5Qwen3.7 Max
HLE
65.0Claude Fable 5.1
41.4Qwen3.7 Max
GPQA
93.7Claude Fable 5.1
92.4Qwen3.7 Max
Terminal-Bench
91.4Claude Fable 5.1
69.7Qwen3.7 Max
GDPval-AA
1853.0Claude Fable 5.1
1546.0Qwen3.7 Max
Finance Agent
58.9Claude Fable 5.1
48.4Qwen3.7 Max
Claude Fable 5.1
Input$10.0
Output$50.0
Workload$20
Context1M
Qwen3.7 Max
Input$2.50
Output$7.50
Workload$4.00
Context1M

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

More Claude Fable 5.1 and Qwen3.7 Max comparisons

Explore how Claude Fable 5.1 and Qwen3.7 Max 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.