MiniMax M1 vs Mistral Large 2407
MiniMax M1 leads Mistral Large 2407 on the Artificial Analysis Intelligence Index, 11.7 to 7.6, and MiniMax M1 costs 2.7x less per output token ($2.20 vs $6.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
MiniMax M1 or Mistral Large 2407: 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 131K tokens).
- Shared results
- 1
- MiniMax M1 only
- 28
- Mistral Large 2407 only
- 16
- Like-for-like categories
- 1 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 7.6.
Same board, both measured
Long documents
Listed context window
MiniMax M1
MiniMax M1 takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
MiniMax M1 $0.0015, Mistral Large 2407 $0.0050 per turn.
List prices
At a glance
- Coding index
- MiniMax M1 not benchmarked, Mistral Large 2407 not benchmarked.
- Widest category
- Intelligence, 4.1 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: MiniMax M1 11.7 against Mistral Large 2407 7.6, 4.1 points apart on a 0 to 100 scale.
- Output price
- MiniMax M1 $2.20 against Mistral Large 2407 $6.00 per million output tokens, 2.7x apart.
- Context window
- MiniMax M1 takes 1M tokens, Mistral Large 2407 131K.
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 2407 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 26.7% | Only Mistral Large 2407 measured |
| LMArena Text: coding | 1359 | Not measured | Only MiniMax M1 measured |
| LMArena Text: software and IT | 1359 | Not measured | Only MiniMax M1 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 M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.7 | 7.6 | MiniMax M1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 33.0% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 47.2% | Only Mistral Large 2407 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 2.9% | Only Mistral Large 2407 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 49.0% | Only Mistral Large 2407 measured |
| SimpleBench | Not measured | 22.5% | Only Mistral Large 2407 measured |
| LMArena Text: hard prompts | 1339 | Not measured | Only MiniMax M1 measured |
| LMArena Text: expert | 1317 | Not measured | Only MiniMax M1 measured |
| LMArena Text: hard prompts in English | 1353 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 0.0 | Only Mistral Large 2407 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 0.0% | Only Mistral Large 2407 measured |
| OTIS Mock AIME | Not measured | 8.5% | Only Mistral Large 2407 measured |
| MATH level 5 | Not measured | 44.8% | Only Mistral Large 2407 measured |
| LMArena Text: math | 1361 | Not measured | Only MiniMax M1 measured |
| LMArena Text: mathematical work | 1363 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 68.3% | Only Mistral Large 2407 measured |
| MMLU | Not measured | 80.0% | Only Mistral Large 2407 measured |
| LMArena Text: science | 1354 | Not measured | Only MiniMax M1 measured |
| LMArena Text: medicine and healthcare | 1355 | Not measured | Only MiniMax M1 measured |
| LMArena Text: legal and government | 1337 | Not measured | Only MiniMax M1 measured |
| LMArena Text: business and finance | 1319 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | Leader |
|---|---|---|---|
| IFBench | Not measured | 31.6% | Only Mistral Large 2407 measured |
| Long context reasoning (AA-LCR) | Not measured | 2.0% | Only Mistral Large 2407 measured |
| DTBench | Not measured | 61.2% | Only Mistral Large 2407 measured |
| Creative writing (Lech Mazur) | Not measured | 69.0% | Only Mistral Large 2407 measured |
| LMArena Text | 1343 | Not measured | Only MiniMax M1 measured |
| LMArena Text: instruction following | 1312 | Not measured | Only MiniMax M1 measured |
| LMArena Text: creative writing | 1297 | Not measured | Only MiniMax M1 measured |
| LMArena Text: English | 1363 | Not measured | Only MiniMax M1 measured |
| LMArena Text: non-English | 1319 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Chinese | 1360 | Not measured | Only MiniMax M1 measured |
| LMArena Text: German | 1350 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Japanese | 1217 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Korean | 1266 | Not measured | Only MiniMax M1 measured |
| LMArena Text: French | 1370 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Spanish | 1353 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Russian | 1329 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Polish | 1329 | Not measured | Only MiniMax M1 measured |
| LMArena Text: multi-turn | 1335 | Not measured | Only MiniMax M1 measured |
| LMArena Text: longer queries | 1326 | Not measured | Only MiniMax M1 measured |
| LMArena Text: writing and language | 1311 | Not measured | Only MiniMax M1 measured |
| LMArena Text: entertainment and media | 1303 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Mistral Large 2407 | 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 2407 |
|---|---|---|
| Maker | MiniMax | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | November 19, 2024 |
| Context window | 1M | 131K |
| 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 2407 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 131K tokens).
Which is cheaper, MiniMax M1 or Mistral Large 2407?
MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Mistral Large 2407 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 2407?
MiniMax M1, with 1M tokens against 131K.
How many benchmarks is the MiniMax M1 vs Mistral Large 2407 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.