Model comparison
DeepSeek-V3.1-Terminus vs MiniMax M1
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 40.3 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
MiniMaxSummary
- They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 6 categories and MiniMax M1 in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 53.1.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $0.55 / $2.20 for MiniMax M1.
- MiniMax M1 accepts more context: 1M tokens versus 164K.
Side by side
| DeepSeek-V3.1-Terminus | MiniMax M1 | |
|---|---|---|
| Provider | DeepSeek | MiniMax |
| Noometry Index | 43.1 | 40.3 |
| Released | 2025-09-22 | 2025-06-13 |
| Weights | Open | Open |
| Context window | 164K | 1M |
| Max output | 147K | 40K |
| Input $ / M tokens | $0.27 | $0.55 |
| Output $ / M tokens | $1 | $2.20 |
| Results tracked | 16 | 18 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), MiniMax M1: 39.9 (#153)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Coding | 1426 | 1359 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning Too close to call
DeepSeek-V3.1-Terminus: 26.4 (#133), MiniMax M1: 26.9 (#126)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1339 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math Too close to call
DeepSeek-V3.1-Terminus: 38.5 (#137), MiniMax M1: 37.5 (#151)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Math | 1402 | 1361 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, MiniMax M1: 36.4 (#170)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Expert | — | 1317 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), MiniMax M1: 45.8 (#163)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Non-English | 1407 | 1319 |
| LMArena Russian | 1436 | 1329 |
| LMArena Chinese | — | 1360 |
| LMArena French | — | 1370 |
| LMArena German | — | 1350 |
| LMArena Japanese | — | 1217 |
| LMArena Korean | — | 1266 |
| LMArena Spanish | — | 1353 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), MiniMax M1: 69.3 (#174)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1312 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), MiniMax M1: 41.4 (#141)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Longer Query | 1421 | 1326 |
| Fiction.LiveBench | — | 69.4% |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), MiniMax M1: 53.1 (#161)
| Benchmark | DeepSeek-V3.1-Terminus | MiniMax M1 |
|---|---|---|
| LMArena Text | 1419 | 1343 |
| LMArena Creative Writing | 1403 | 1298 |
| LMArena Multi-Turn | 1411 | 1335 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than MiniMax M1?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 40.3 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1-Terminus or MiniMax M1?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; MiniMax M1 lists at $0.55 and $2.20.
Is DeepSeek-V3.1-Terminus or MiniMax M1 better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
MiniMax M1 does, with 1M tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and MiniMax M1 share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and MiniMax M1 has 18.