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Mercury 2.5 vs MiniMax M2.1

MiniMax M2.1 leads Mercury 2.5 on the Artificial Analysis Intelligence Index, 20.9 to 12.3, and Mercury 2.5 costs 8.0x less per output token ($0.15 vs $1.20 per million). Updated October 22, 2026; 7 benchmarks have a result for both.

Mercury 2.5Inception
Coding
1.6
Overall
No data
Output $/M
$0.15
2
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
5
vs boards won of 7 shared

Mercury 2.5 or MiniMax M2.1: which to pick

Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding.

Pick MiniMax M2.1 for work measured by ALE-Bench or AA Intelligence Index, where it leads.

Shared results
7
Mercury 2.5 only
15
MiniMax M2.1 only
27
Like-for-like categories
5 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
Mercury 2.5 1.6 from 2 benchmarks, MiniMax M2.1 not benchmarked.
Widest category
General, 14.8 points apart on average over 2 shared benchmarks.
Widest single gap
MedScribe (Vals AI): Mercury 2.5 55.1% against MiniMax M2.1 80.8%, 25.7 points apart on a 0 to 100 scale.
Output price
Mercury 2.5 $0.15 against MiniMax M2.1 $1.20 per million output tokens, 8.0x apart.
Context window
Mercury 2.5 takes 260K 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
CategoryMercury 2.5BarsMiniMax M2.1Ties
Coding01
Intelligence01
Reasoning01
Knowledge11
General11
All shared boards25
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax 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
Terminal-Bench 4 (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
Vibe Code Bench (Vals AI)3.7%Not measuredOnly Mercury 2.5 measured
Code migration (Vals AI)4.5%Not measuredOnly Mercury 2.5 measured
IOI (Vals AI)2.4%Not measuredOnly Mercury 2.5 measured
Terminal-Bench 2.1 (Vals AI)34.5%Not measuredOnly Mercury 2.5 measured
SkillsBench (Vals AI)18.1%Not measuredOnly Mercury 2.5 measured
CyberBench (Vals AI)45.5%Not measuredOnly Mercury 2.5 measured
LiveCodeBench (Artificial Analysis run)Not measured81.0%Only MiniMax M2.1 measured
SciCode38.5%Not measuredOnly Mercury 2.5 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-Bench301.6623.8MiniMax M2.1
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax M2.1Leader
AA Intelligence Index12.320.9MiniMax M2.1
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax M2.1Leader
Finance Agent (Vals AI)18.9%Not measuredOnly Mercury 2.5 measured
Tax Agent Bench (Vals AI)2.5%Not measuredOnly Mercury 2.5 measured
Legal Research Bench (Vals AI)4.3%Not measuredOnly Mercury 2.5 measured
Excel Modeling Benchmark (Vals AI)8.8%Not measuredOnly Mercury 2.5 measured
Terminal-Bench-Science (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
τ²-Bench TelecomNot measured85.4%Only MiniMax M2.1 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax 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)11.8%23.2%MiniMax M2.1
Neither model has a result on the other 20 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax 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
ProofBench3.0%Not measuredOnly Mercury 2.5 measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
Knowledge benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax M2.1Leader
MMLU ProNot measured87.0%Only MiniMax M2.1 measured
LegalBench (Vals AI)83.1%75.5%Mercury 2.5
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)31.3%34.1%MiniMax M2.1
MMLU Pro (Artificial Analysis run)Not measured87.5%Only MiniMax M2.1 measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax 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
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax M2.1Leader
Public Benefits Bench (Vals AI)45.3%Not measuredOnly Mercury 2.5 measured
MedScribe (Vals AI)55.1%80.8%MiniMax M2.1
IFBenchNot measured69.9%Only MiniMax M2.1 measured
Long context reasoning (AA-LCR)71.7%67.7%Mercury 2.5
Neither model has a result on the other 44 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mercury 2.5 and MiniMax M2.1
BenchmarkMercury 2.5MiniMax 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

Mercury 2.5$0.0001Fits in one request
MiniMax M2.1$0.0009Fits in one request

Mercury 2.5 costs less

Repository review

50K input + 3K output tokens

Mercury 2.5$0.0024Fits in one request
MiniMax M2.1$0.019Fits in one request

Mercury 2.5 costs less

Agent loop

200K input + 10K output tokens

Mercury 2.5$0.0095Fits in one request
MiniMax M2.1$0.072Exceeds the context window

Mercury 2.5 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 Mercury 2.5 and MiniMax M2.1
SpecificationInception Mercury 2.5MiniMax M2.1
MakerInceptionMiniMax
WeightsNo public weights listedOpen weights
ReleasedSeptember 8, 2026December 23, 2025
Context window260K205K
Input $/Mtok$0.04$0.30
Output $/Mtok$0.15$1.20
Coding index1.6Not benchmarked
Independent measurements behind it21
Cost per solved taskNot computable$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2.5 better than MiniMax M2.1 for coding?

Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding. Pick MiniMax M2.1 for work measured by ALE-Bench or AA Intelligence Index, where it leads.

Which is cheaper, Mercury 2.5 or MiniMax M2.1?

Mercury 2.5 costs $0.04 per million input tokens and $0.15 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, Mercury 2.5 or MiniMax M2.1?

Mercury 2.5, with 260K tokens against 205K.

How many benchmarks is the Mercury 2.5 vs MiniMax M2.1 comparison based on?

7 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 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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