GPT-5.1-Codex-Max vs Grok 4.20 Multi-Agent

The 68/100 score advantage likely stems from Grok's massive 2.0M token context window (5x larger) and superior file handling modality, which are critical for complex coding tasks involving large codebases. Function calling becomes less essential when you can fit entire repositories in context and directly process file inputs, explaining why Grok ranks #4 despite missing this feature.

For projects exceeding 400K tokens, Grok becomes essential since GPT-5.1-Codex-Max hits its context limit, but the real value emerges in output-heavy workloads where Grok's $6/M output pricing beats GPT-5.1's $10/M by 40%. A typical 1M token analysis job would cost $8 on Grok versus $11.25 on GPT-5.1, making Grok cheaper for large-scale code generation despite higher input costs.

The 128K guaranteed output is crucial for generating complete modules or documentation in one shot, while Grok's null value suggests either no hard limit or undisclosed constraints. Given Grok's 11-position rank advantage (#4 vs #15), the lack of output specification hasn't hurt real-world performance, indicating either generous limits or that most coding tasks don't approach 128K tokens anyway.

Migration requires rewriting function-based workflows into prompt-based equivalents, but Grok's 2.0M context window allows embedding entire API schemas and examples directly, potentially yielding better results than GPT-5.1's function abstractions. The 7-point score gap and $4/M output savings justify migration costs for teams processing over 500K tokens monthly.