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Comprehensive side-by-side LLM comparison
Minimax M 2.5 leads with 5.8% higher average benchmark score. Overall, Minimax M 2.5 is the stronger choice for coding tasks.
MiniMax
MiniMax M2.5 is a large language model from MiniMax extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. It targets agentic tool use, coding automation, and office productivity tasks, with strong results on software engineering and web browsing benchmarks. M2.5 represents the next generation of MiniMax's M-series models optimized for production agentic workloads.
StepFun
Step-3.5-Flash, released by StepFun on February 2, 2026, is a Mixture-of-Experts large language model with 197 billion total parameters and approximately 11 billion active parameters per inference. It features a 256K token context window using a 3:1 sliding-window-to-full-attention ratio, processing 100–350 tokens per second. Step-3.5-Flash targets agentic tasks, coding workflows, and open-source deployments requiring frontier reasoning capabilities with efficient inference, under an Apache 2.0 license.
11 days newer
Step-3.5-Flash
StepFun
2026-02-02
Minimax M 2.5
MiniMax
2026-02-13
Context window and performance specifications
Average performance across 1 common benchmarks
Minimax M 2.5
Step-3.5-Flash
Performance comparison across key benchmark categories
Minimax M 2.5
Step-3.5-Flash
Available providers and their performance metrics
Minimax M 2.5
MiniMax
Step-3.5-Flash
Minimax M 2.5
Step-3.5-Flash
Minimax M 2.5
Step-3.5-Flash