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MiniMax M1 vs MiniMax M2.1

MiniMax M2.1 leads MiniMax M1 on the Artificial Analysis Intelligence Index, 20.9 to 11.7, and MiniMax M2.1 costs 1.8x less per output token ($1.20 vs $2.20 per million). Updated October 22, 2026; 1 benchmarks have a result for both.

MiniMax M1MiniMax
Coding
No data
Overall
No data
Output $/M
$2.20
0
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
1
vs boards won of 1 shared

MiniMax M1 or MiniMax M2.1: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick MiniMax M1 for a larger context window (1M against 205K tokens) and work measured by AA Intelligence Index, where it leads.

Shared results
1
MiniMax M1 only
28
MiniMax M2.1 only
33
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.

At a glance

Coding index
MiniMax M1 not benchmarked, MiniMax M2.1 not benchmarked.
Widest category
Intelligence, 9.2 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: MiniMax M1 11.7 against MiniMax M2.1 20.9, 9.2 points apart on a 0 to 100 scale.
Output price
MiniMax M1 $2.20 against MiniMax M2.1 $1.20 per million output tokens, 1.8x apart.
Context window
MiniMax M1 takes 1M tokens, MiniMax M2.1 205K.

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.

Boards won, where both have a result
CategoryMiniMax M1BarsMiniMax M2.1Ties
Intelligence01
All shared boards01
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
LiveCodeBench (Vals AI)Not measured81.8%Only MiniMax M2.1 measured
SWE-bench Verified (Vals AI)Not measured74.8%Only MiniMax M2.1 measured
LiveCodeBench (Artificial Analysis run)Not measured81.0%Only MiniMax M2.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only MiniMax M2.1 measured
Terminal-BenchNot measured36.6%Only MiniMax M2.1 measured
ALE-BenchNot measured623.8Only MiniMax M2.1 measured
LMArena Text: coding1359Not measuredOnly MiniMax M1 measured
LMArena Text: software and IT1359Not measuredOnly MiniMax M1 measured
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
AA Intelligence Index11.720.9MiniMax M2.1
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
Agentic work benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
τ²-Bench TelecomNot measured85.4%Only MiniMax M2.1 measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Reasoning benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
GPQA DiamondNot measured78.5%Only MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)Not measured83.0%Only MiniMax M2.1 measured
Humanity's Last Exam (Artificial Analysis run)Not measured23.2%Only MiniMax M2.1 measured
LMArena Text: hard prompts1339Not measuredOnly MiniMax M1 measured
LMArena Text: expert1317Not measuredOnly MiniMax M1 measured
LMArena Text: hard prompts in English1353Not measuredOnly MiniMax M1 measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
AIMENot measured77.9%Only MiniMax M2.1 measured
MATH 500 (Vals AI)Not measured89.0%Only MiniMax M2.1 measured
MGSM (Vals AI)Not measured87.8%Only MiniMax M2.1 measured
AA Math IndexNot measured82.7Only MiniMax M2.1 measured
AIME 2025 (Artificial Analysis run)Not measured82.7%Only MiniMax M2.1 measured
LMArena Text: math1361Not measuredOnly MiniMax M1 measured
LMArena Text: mathematical work1363Not measuredOnly MiniMax M1 measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Knowledge benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
MMLU ProNot measured87.0%Only MiniMax M2.1 measured
LegalBench (Vals AI)Not measured75.5%Only MiniMax M2.1 measured
CaseLaw (Vals AI)Not measured55.8%Only MiniMax M2.1 measured
CorpFin (Vals AI)Not measured58.9%Only MiniMax M2.1 measured
TaxEval (Vals AI)Not measured66.3%Only MiniMax M2.1 measured
MedQA (Vals AI)Not measured91.2%Only MiniMax M2.1 measured
MedCode (Vals AI)Not measured34.1%Only MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)Not measured87.5%Only MiniMax M2.1 measured
LMArena Text: science1354Not measuredOnly MiniMax M1 measured
LMArena Text: medicine and healthcare1355Not measuredOnly MiniMax M1 measured
LMArena Text: legal and government1337Not measuredOnly MiniMax M1 measured
LMArena Text: business and finance1319Not measuredOnly MiniMax M1 measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
Design Arena: websitesNot measured1201Only MiniMax M2.1 measured
Design Arena: UI componentsNot measured1220Only MiniMax M2.1 measured
Design Arena: game devNot measured1134Only MiniMax M2.1 measured
Design Arena: data vizNot measured1206Only MiniMax M2.1 measured
Design Arena: 3DNot measured1164Only MiniMax M2.1 measured
Design Arena: all code categoriesNot measured1190Only MiniMax M2.1 measured
Design Arena: SVGNot measured1131Only 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 index20 boards, none shared
General benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
MedScribe (Vals AI)Not measured80.8%Only MiniMax M2.1 measured
IFBenchNot measured69.9%Only MiniMax M2.1 measured
Long context reasoning (AA-LCR)Not measured67.7%Only MiniMax M2.1 measured
LMArena Text1343Not measuredOnly MiniMax M1 measured
LMArena Text: instruction following1312Not measuredOnly MiniMax M1 measured
LMArena Text: creative writing1297Not measuredOnly MiniMax M1 measured
LMArena Text: English1363Not measuredOnly MiniMax M1 measured
LMArena Text: non-English1319Not measuredOnly MiniMax M1 measured
LMArena Text: Chinese1360Not measuredOnly MiniMax M1 measured
LMArena Text: German1350Not measuredOnly MiniMax M1 measured
LMArena Text: Japanese1217Not measuredOnly MiniMax M1 measured
LMArena Text: Korean1266Not measuredOnly MiniMax M1 measured
LMArena Text: French1370Not measuredOnly MiniMax M1 measured
LMArena Text: Spanish1353Not measuredOnly MiniMax M1 measured
LMArena Text: Russian1329Not measuredOnly MiniMax M1 measured
LMArena Text: Polish1329Not measuredOnly MiniMax M1 measured
LMArena Text: multi-turn1335Not measuredOnly MiniMax M1 measured
LMArena Text: longer queries1326Not measuredOnly MiniMax M1 measured
LMArena Text: writing and language1311Not measuredOnly MiniMax M1 measured
LMArena Text: entertainment and media1303Not measuredOnly MiniMax M1 measured
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
Image generation benchmarks for MiniMax M1 and MiniMax M2.1
BenchmarkMiniMax M1MiniMax M2.1Leader
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$0.0015Fits in one request
MiniMax M2.1$0.0009Fits in one request

MiniMax M2.1 costs less

Repository review

50K input + 3K output tokens

MiniMax M1$0.027Fits in one request
MiniMax M2.1$0.019Fits in one request

MiniMax M2.1 costs less

Agent loop

200K input + 10K output tokens

MiniMax M1$0.102Fits in one request
MiniMax M2.1$0.072Exceeds the context window

MiniMax M2.1 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.

Specifications of MiniMax M1 and MiniMax M2.1
SpecificationMiniMax M1MiniMax M2.1
MakerMiniMaxMiniMax
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025December 23, 2025
Context window1M205K
Input $/Mtok$0.40$0.30
Output $/Mtok$2.20$1.20
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M1 better than MiniMax M2.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for a larger context window (1M against 205K tokens) and work measured by AA Intelligence Index, where it leads.

Which is cheaper, MiniMax M1 or MiniMax M2.1?

MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, MiniMax M1 or MiniMax M2.1?

MiniMax M1, with 1M tokens against 205K.

How many benchmarks is the MiniMax M1 vs MiniMax M2.1 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 MiniMax M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.

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