Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 mini has the cleaner overall profile here, landing at 60 versus 57. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. GPT-4.1 mini gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
Pick GPT-4.1 mini if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-4.1 mini
56.5
MiniMax M2.7
57
GPT-4.1 mini
28.3
MiniMax M2.7
56.2
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4.1 mini is ahead overall, 60 to 57. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 30% and 56.2%.
MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 28.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiniMax M2.7 has the edge for agentic tasks in this comparison, averaging 57 versus 56.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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