MiniMax M2.1 vs Ministral 3 14B 2512
MiniMax M2.1 leads Ministral 3 14B 2512 on the Artificial Analysis Intelligence Index, 20.9 to 6.0, and Ministral 3 14B 2512 costs 6.0x less per output token ($0.20 vs $1.20 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
MiniMax M2.1 or Ministral 3 14B 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- MiniMax M2.1 only
- 29
- Ministral 3 14B 2512 only
- 2
- Like-for-like categories
- 2 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 6.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ministral 3 14B 2512 has a AA Agentic Index result, 1.1.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M2.1 has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only MiniMax M2.1 has a AIME result, 77.9%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.1 has a MMLU Pro result, 87.0%.
Directional only
Web design
Design Arena: websites
MiniMax M2.1
MiniMax M2.1 leads, 1201 against 1081.
Same board, both measured
Long documents
Listed context window
Ministral 3 14B 2512
Ministral 3 14B 2512 takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ministral 3 14B 2512
MiniMax M2.1 $0.0009, Ministral 3 14B 2512 $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.1 has the number, $0.59.
Directional only
At a glance
- Coding index
- MiniMax M2.1 not benchmarked, Ministral 3 14B 2512 not benchmarked.
- Widest category
- Web design, 16.2 points apart on average over 4 shared benchmarks.
- Widest single gap
- Design Arena: 3D: MiniMax M2.1 1164 against Ministral 3 14B 2512 989, 21.9 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.1 $1.20 against Ministral 3 14B 2512 $0.20 per million output tokens, 6.0x apart.
- Context window
- MiniMax M2.1 takes 205K tokens, Ministral 3 14B 2512 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | MiniMax M2.1 | Bars | Ministral 3 14B 2512 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Web design | 4 | 0 | ||
| All shared boards | 5 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 14.4 | Only Ministral 3 14B 2512 measured |
| LiveCodeBench (Vals AI) | 81.8% | Not measured | Only MiniMax M2.1 measured |
| SWE-bench Verified (Vals AI) | 74.8% | Not measured | Only MiniMax M2.1 measured |
| LiveCodeBench (Artificial Analysis run) | 81.0% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 28.8% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench | 36.6% | Not measured | Only MiniMax M2.1 measured |
| ALE-Bench | 623.8 | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.9 | 6.0 | MiniMax M2.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.1 | Only Ministral 3 14B 2512 measured |
| τ²-Bench Telecom | 85.4% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only MiniMax M2.1 measured |
| GPQA Diamond (Artificial Analysis run) | 83.0% | Not measured | Only MiniMax M2.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.2% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AIME | 77.9% | Not measured | Only MiniMax M2.1 measured |
| MATH 500 (Vals AI) | 89.0% | Not measured | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | 87.8% | Not measured | Only MiniMax M2.1 measured |
| AA Math Index | 82.7 | Not measured | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | 82.7% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | Not measured | Only MiniMax M2.1 measured |
| LegalBench (Vals AI) | 75.5% | Not measured | Only MiniMax M2.1 measured |
| CaseLaw (Vals AI) | 55.8% | Not measured | Only MiniMax M2.1 measured |
| CorpFin (Vals AI) | 58.9% | Not measured | Only MiniMax M2.1 measured |
| TaxEval (Vals AI) | 66.3% | Not measured | Only MiniMax M2.1 measured |
| MedQA (Vals AI) | 91.2% | Not measured | Only MiniMax M2.1 measured |
| MedCode (Vals AI) | 34.1% | Not measured | Only MiniMax M2.1 measured |
| MMLU Pro (Artificial Analysis run) | 87.5% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1201 | 1081 | MiniMax M2.1 |
| Design Arena: UI components | 1220 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: game dev | 1134 | 1037 | MiniMax M2.1 |
| Design Arena: data viz | 1206 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: 3D | 1164 | 989 | MiniMax M2.1 |
| Design Arena: all code categories | 1190 | 1064 | MiniMax M2.1 |
| Design Arena: SVG | 1131 | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 80.8% | Not measured | Only MiniMax M2.1 measured |
| IFBench | 69.9% | Not measured | Only MiniMax M2.1 measured |
| Long context reasoning (AA-LCR) | 67.7% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.1 | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Ministral 3 14B 2512 costs less
Repository review
50K input + 3K output tokens
Ministral 3 14B 2512 costs less
Agent loop
200K input + 10K output tokens
Ministral 3 14B 2512 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | MiniMax M2.1 | Mistral Ministral 3 14B 2512 |
|---|---|---|
| Maker | MiniMax | Mistral AI |
| Weights | Open weights | Open weights |
| Released | December 23, 2025 | December 2, 2025 |
| Context window | 205K | 262K |
| Input $/Mtok | $0.30 | $0.20 |
| Output $/Mtok | $1.20 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.59 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.1 better than Ministral 3 14B 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, MiniMax M2.1 or Ministral 3 14B 2512?
MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; Ministral 3 14B 2512 costs $0.20 and $0.20. Cost per solved task is known for MiniMax M2.1 only.
Which has the bigger context window, MiniMax M2.1 or Ministral 3 14B 2512?
Ministral 3 14B 2512, with 262K tokens against 205K.
How many benchmarks is the MiniMax M2.1 vs Ministral 3 14B 2512 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark and Ministral 3 14B 2512's on 0. Where only one model has a result, the page says so instead of naming a winner.