Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-1M is clearly ahead on the aggregate, 67 to 57. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-1M's sharpest advantage is in agentic, where it averages 64.7 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 57% to 65%. MiniMax M2.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
MiniMax M2.7 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5-1M. That is roughly Infinityx on output cost alone. Qwen2.5-1M gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
Pick Qwen2.5-1M if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if coding is the priority.
MiniMax M2.7
57
Qwen2.5-1M
64.7
MiniMax M2.7
56.2
Qwen2.5-1M
44.9
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.
Qwen2.5-1M is ahead overall, 67 to 57. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 57% and 65%.
MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 44.9. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for agentic tasks in this comparison, averaging 64.7 versus 57. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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