MiniMax M1 vs Mistral Large
MiniMax M1 leads Mistral Large on the Artificial Analysis Intelligence Index, 11.7 to 5.8, and MiniMax M1 costs 2.7x less per output token ($2.20 vs $6.00 per million). Updated October 21, 2026; 29 benchmarks have a result for both.
MiniMax M1 or Mistral Large: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M1 for output tokens 2.7x cheaper ($2.20 vs $6.00 per million) and a larger context window (1M against 128K tokens).
- Shared results
- 29
- MiniMax M1 only
- 0
- Mistral Large only
- 15
- Like-for-like categories
- 6 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 M1
MiniMax M1 leads, 11.7 against 5.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Long documents
Listed context window
MiniMax M1
MiniMax M1 takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
MiniMax M1 $0.0015, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- MiniMax M1 not benchmarked, Mistral Large not benchmarked.
- Widest category
- Math, 17.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: Polish: MiniMax M1 1329 against Mistral Large 1157, 28.7 points apart on a 0 to 100 scale.
- Output price
- MiniMax M1 $2.20 against Mistral Large $6.00 per million output tokens, 2.7x apart.
- Context window
- MiniMax M1 takes 1M tokens, Mistral Large 128K.
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 M1 | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 17 | 0 | ||
| All shared boards | 29 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| LMArena Text: coding | 1359 | 1275 | MiniMax M1 |
| LMArena Text: software and IT | 1359 | 1274 | MiniMax M1 |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.7 | 5.8 | MiniMax M1 |
| Epoch Capabilities Index | Not measured | 122.1 | Only Mistral Large measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 35.1% | Only Mistral Large measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.5% | Only Mistral Large measured |
| LMArena Text: hard prompts | 1339 | 1257 | MiniMax M1 |
| LMArena Text: expert | 1317 | 1208 | MiniMax M1 |
| LMArena Text: hard prompts in English | 1353 | 1268 | MiniMax M1 |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| LMArena Text: math | 1361 | 1261 | MiniMax M1 |
| LMArena Text: mathematical work | 1363 | 1257 | MiniMax M1 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1354 | 1260 | MiniMax M1 |
| LMArena Text: medicine and healthcare | 1355 | 1255 | MiniMax M1 |
| LMArena Text: legal and government | 1337 | 1275 | MiniMax M1 |
| LMArena Text: business and finance | 1319 | 1238 | MiniMax M1 |
| Neither model has a result on the other 9 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
| Benchmark | MiniMax M1 | Mistral Large | Leader |
|---|---|---|---|
| DTBench | Not measured | 60.8% | Only Mistral Large measured |
| LMArena Text | 1343 | 1265 | MiniMax M1 |
| LMArena Text: instruction following | 1312 | 1249 | MiniMax M1 |
| LMArena Text: creative writing | 1297 | 1242 | MiniMax M1 |
| LMArena Text: English | 1363 | 1284 | MiniMax M1 |
| LMArena Text: non-English | 1319 | 1235 | MiniMax M1 |
| LMArena Text: Chinese | 1360 | 1239 | MiniMax M1 |
| LMArena Text: German | 1350 | 1242 | MiniMax M1 |
| LMArena Text: Japanese | 1217 | 1170 | MiniMax M1 |
| LMArena Text: Korean | 1266 | 1202 | MiniMax M1 |
| LMArena Text: French | 1370 | 1325 | MiniMax M1 |
| LMArena Text: Spanish | 1353 | 1268 | MiniMax M1 |
| LMArena Text: Russian | 1329 | 1252 | MiniMax M1 |
| LMArena Text: Polish | 1329 | 1157 | MiniMax M1 |
| LMArena Text: multi-turn | 1335 | 1260 | MiniMax M1 |
| LMArena Text: longer queries | 1326 | 1261 | MiniMax M1 |
| LMArena Text: writing and language | 1311 | 1261 | MiniMax M1 |
| LMArena Text: entertainment and media | 1303 | 1230 | MiniMax M1 |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large | 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
MiniMax M1 costs less
Repository review
50K input + 3K output tokens
MiniMax M1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M1 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 M1 | Mistral Large |
|---|---|---|
| Maker | MiniMax | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | February 26, 2024 |
| Context window | 1M | 128K |
| Input $/Mtok | $0.40 | $2.00 |
| Output $/Mtok | $2.20 | $6.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M1 better than Mistral Large for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for output tokens 2.7x cheaper ($2.20 vs $6.00 per million) and a larger context window (1M against 128K tokens).
Which is cheaper, MiniMax M1 or Mistral Large?
MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, MiniMax M1 or Mistral Large?
MiniMax M1, with 1M tokens against 128K.
How many benchmarks is the MiniMax M1 vs Mistral Large comparison based on?
29 benchmarks have a result for both models as of October 21, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.