LLM Comparison

Claude Fable 5.1 vs MiMo-V2.5-Pro: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5.1 vs MiMo-V2.5-Pro 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: Claude Fable 5.1 ranks higher (#2 vs #51) and wins 5 of 5 shared benchmarks.

Rank #2 vs #51AskClash overall scores 78.2 vs 36.0.
Pricing $10.0/$50.0 vs —/—Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs Xiaomi.

Claude Fable 5.1 vs MiMo-V2.5-Pro benchmark comparison

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

MetricClaude Fable 5.1MiMo-V2.5-Pro
Overall Score78.236.0
Leaderboard Rank#2#51
ACB79.2—
RWT9.0—
Coding Agent Index62.2—
HLE65.048.0
GPQA93.766.7
IFEval—79.9
SWE-bench—78.9
SWE-Pro81.257.2
SWE-Atlas64.8—
Terminal-Bench52.0—
DeepSWE67.4—
GDPval-AA1853.01123.5
Finance Agent58.941.5
MMMU-Pro90.6—
ARC-AGI 290.0—
Tau2—94.2
Input Price (per 1M tokens)$10.0—
Output Price (per 1M tokens)$50.0—
Context Window1M1M
Benchmarks Published158

Claude Fable 5.1 vs MiMo-V2.5-Pro head-to-head charts

Claude Fable 5.1 leads 6 and MiMo-V2.5-Pro leads 0 of 6 shared benchmarks. Charts show only benchmarks both models publish.

Claude Fable 5.1MiMo-V2.5-Pro
Overall
78.2Claude Fable 5.1
36.0MiMo-V2.5-Pro
HLE
65.0Claude Fable 5.1
48.0MiMo-V2.5-Pro
GPQA
93.7Claude Fable 5.1
66.7MiMo-V2.5-Pro
SWE-Pro
81.2Claude Fable 5.1
57.2MiMo-V2.5-Pro
GDPval-AA
1853.0Claude Fable 5.1
1123.5MiMo-V2.5-Pro
Finance Agent
58.9Claude Fable 5.1
41.5MiMo-V2.5-Pro
Claude Fable 5.1
Input$10.0
Output$50.0
Workload$20
Context1M
MiMo-V2.5-Pro
Input—
Output—
Workload—
Context1M

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

More Claude Fable 5.1 and MiMo-V2.5-Pro comparisons

Explore how Claude Fable 5.1 and MiMo-V2.5-Pro 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.