Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
MiniMax M3
76
Qwen3.6-27B
73
Verified leaderboard positions: MiniMax M3 #12 · Qwen3.6-27B #18
Pick MiniMax M3 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Agentic
+12.6 difference
Coding
+3.6 difference
Multimodal
+11.7 difference
MiniMax M3
Qwen3.6-27B
$0.3 / $1.2
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick MiniMax M3 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
MiniMax M3 has the cleaner provisional overall profile here, landing at 76 versus 73. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MiniMax M3's sharpest advantage is in agentic, where it averages 71.9 against 59.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 66% to 59.3%. Qwen3.6-27B does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
MiniMax M3 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 Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while MiniMax M3 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. MiniMax M3 gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 76 to 73. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 66% and 59.3%.
Qwen3.6-27B has the edge for coding in this comparison, averaging 70.6 versus 67. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 71.9 versus 59.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.6 versus 64.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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