Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiniMax M2.7 is clearly ahead on the aggregate, 57 to 41. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M2.7's sharpest advantage is in agentic, where it averages 57 against 34.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 41% to 57%.
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 DBRX Instruct. That is roughly Infinityx on output cost alone. MiniMax M2.7 gives you the larger context window at 200K, compared with 32K for DBRX Instruct.
Pick MiniMax M2.7 if you want the stronger benchmark profile. DBRX Instruct only becomes the better choice if you want the cheaper token bill.
DBRX Instruct
34.3
MiniMax M2.7
57
DBRX Instruct
48
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.
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Benchmark data for this category is coming soon.
MiniMax M2.7 is ahead overall, 57 to 41. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41% and 57%.
MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 48. 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 34.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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