MiniMax M2.7 vs SWE-1.7
Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verdict
SWE-1.7 leads for most workloads.
Based on BenchLM composite scores, July 2026.
MiniMax M2.7
56
SWE-1.7
75
Pick SWE-1.7 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Category Radar
Head-to-Head by Category
Category Breakdown
| Benchmark | MiniMax M2.7 | Δ | SWE-1.7 |
|---|---|---|---|
| Agentic | 57.0 | → 24.5 | 81.5 |
| Coding | 54.4 | — | — |
Operational Comparison
MiniMax M2.7
SWE-1.7
$0.3 / $1.2
N/A
45 t/s
N/A
2.53s
N/A
200K
256K
Quick Verdict
Pick SWE-1.7 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
SWE-1.7 is clearly ahead on the provisional aggregate, 75 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
SWE-1.7's sharpest advantage is in agentic, where it averages 81.5 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 57% to 81.5%.
SWE-1.7 is the reasoning model in the pair, while MiniMax M2.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. SWE-1.7 gives you the larger context window at 256K, compared with 200K for MiniMax M2.7.
Benchmark Deep Dive
Frequently Asked Questions (2)
Which is better, MiniMax M2.7 or SWE-1.7?
SWE-1.7 is ahead on BenchLM's provisional leaderboard, 75 to 56. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 57% and 81.5%.
Which is better for agentic tasks, MiniMax M2.7 or SWE-1.7?
SWE-1.7 has the edge for agentic tasks in this comparison, averaging 81.5 versus 57. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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