MiniMax-M1 is a hybrid MoE reasoning model with 40K thinking budget. World's first open-weight, large-scale hybrid-attention model with lightning attention for efficient test-time compute scaling. Excels at complex tasks requiring extensive reasoning.
Added Jan 8, 2025
Context Window
1.0M
Max Output
131.1K
Input Price (Auto)
$0.14/1M
Output Price (Auto)
$1.33/1M
Cache Read (Auto)
$0.070/1M
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from LMArena.
Arena Score
1363.9
Overall Rank
#188 / 401
Votes
34,024
Confidence Interval
1359.6 - 1368.2
Category Scores
Coding
#182 / 396
6,331 votes
1416.4
Math
#181 / 384
1,762 votes
1369.7
Longer Query
#195 / 379
6,913 votes
1363.1
Creative Writing
#199 / 399
4,449 votes
1319.1
Instruction Following
#193 / 401
8,544 votes
1346.0
Hard Prompts
#188 / 401
15,487 votes
1380.5
Additional Categories22
German
#155 / 299
875 votes
1362.7
French
#157 / 281
465 votes
1395.0
Polish
#166 / 222
3,520 votes
1352.3
Spanish
#173 / 283
825 votes
1366.6
Industry Mathematical
#175 / 378
1,732 votes
1378.5
Korean
#177 / 269
659 votes
1283.2
Industry Medicine And Healthcare
#179 / 369
2,078 votes
1391.4
English
#181 / 401
14,816 votes
1384.8
Chinese
#185 / 372
2,338 votes
1386.6
Industry Life And Physical And Social Science
#187 / 399
5,763 votes
1381.7
Industry Software And It Services
#188 / 401
11,121 votes
1402.5
Exclude Ties
#189 / 401
23,910 votes
1329.0
Industry Entertainment And Sports And Media
#189 / 399
6,180 votes
1325.3
Multi Turn
#189 / 399
5,423 votes
1356.9
Hard Prompts English
#190 / 399
6,941 votes
1395.7
Russian
#190 / 365
2,366 votes
1351.2
Japanese
#194 / 265
824 votes
1233.9
Expert
#195 / 350
1,584 votes
1363.5
Non English
#195 / 401
19,199 votes
1340.4
Industry Business And Management And Financial Operations
#199 / 394
5,990 votes
1351.6
Industry Writing And Literature And Language
#200 / 400
7,634 votes
1332.0
Industry Legal And Government
#202 / 373
2,329 votes
1364.0
Published 2026-09-11 · Matched as minimax-m1
LMArena DatasetProviders
Auto routing is available for this model. Explicit provider selection is not available.
Loading provider options…
Related text models
Compare MiniMax M1 with similar models from the same provider or model family.
MiniMax M3
minimax/minimax-m3MiniMax M3 is the non-thinking route for MiniMax's open-weights frontier model, built for coding, agent workflows, tool use, and multimodal understanding from step zero. It keeps native thinking disabled for faster direct answers. MiniMax reports 59.0% on SWE-Bench Pro and 66.0% on Terminal Bench 2.1, with Sparse Attention designed to scale context to 1M. It starts with a 512K context cap on NanoGPT for now.
MiniMax M3 Thinking
minimax/minimax-m3:thinkingMiniMax M3 Thinking is the adaptive-thinking version of MiniMax's open-weights frontier model for coding, agent workflows, tool use, long-context tasks, and native multimodal understanding. MiniMax reports 59.0% on SWE-Bench Pro and 66.0% on Terminal Bench 2.1, with Sparse Attention designed to scale context to 1M. It starts with a 512K context cap on NanoGPT for now.
MiniMax Latest
minimax/minimax-latestCompatibility alias that routes to the newest MiniMax text model. Currently routes to MiniMax M3 (adaptive thinking).
MiniMax M2.7
minimax/minimax-m2.7MiniMax M2.7 is the first model deeply involved in iterating on its own training. It excels in real-world software engineering (SWE-Pro 56.22%), end-to-end project delivery (VIBE-Pro 55.6%), and complex office workflows with strong tool-use compliance and agentic capabilities.
MiniMax M2.7 Turbo
minimax/minimax-m2.7-turboMiniMax M2.7 Turbo is the highspeed and higher priced route for M2.7.
MiniMax M2.5
minimax/minimax-m2.5MiniMax M2.5 is a productivity-focused flagship model that builds on M2.1 with stronger coding and real-world office workflow performance (Word, Excel, PowerPoint), plus better tool-use planning and token efficiency.