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GLM 4.5 vs MiniMax M2

MiniMax M2 leads GLM 4.5 on the Artificial Analysis Intelligence Index, 18.6 to 12.8, and MiniMax M2 costs 2.2x less per output token ($1.02 vs $2.20 per million). Updated October 22, 2026; 46 benchmarks have a result for both.

Replace GLM 4.5 Replace MiniMax M2
GLM 4.5Z.ai
Coding
No data
Overall
No data
Output $/M
$2.20
36
MiniMax M2MiniMax
Coding
No data
Overall
No data
Output $/M
$1.02
10
vs boards won of 46 shared

GLM 4.5 or MiniMax M2: which to pick

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

Pick GLM 4.5 for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGLM 4.5Z.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M2MiniMaxNot benchmarked1 independent benchmark$0.702 per solved task
Shared results
46
GLM 4.5 only
15
MiniMax M2 only
4
Like-for-like categories
8 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
GLM 4.5 not benchmarked, MiniMax M2 not benchmarked.
Widest category
Agentic work, 43.9 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 43.0% against MiniMax M2 86.8%, 43.9 points apart on a 0 to 100 scale.
Output price
GLM 4.5 $2.20 against MiniMax M2 $1.02 per million output tokens, 2.2x apart.
Context window
GLM 4.5 takes 131K tokens, MiniMax M2 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
CategoryGLM 4.5BarsMiniMax M2Ties
Coding32
Intelligence01
Agentic work01
Reasoning51
Math22
Knowledge50
Web design61
General152
All shared boards3610
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
SWE-bench Verified64.2%61.0%GLM 4.5
LMArena WebDevNot measured1297Only MiniMax M2 measured
LiveCodeBench (Vals AI)67.5%Not measuredOnly GLM 4.5 measured
LiveCodeBench (Artificial Analysis run)73.8%82.6%MiniMax M2
Terminal-Bench Hard (Artificial Analysis run)22.0%25.8%MiniMax M2
Terminal-BenchNot measured30.0%Only MiniMax M2 measured
WeirdML40.6%Not measuredOnly GLM 4.5 measured
ALE-Bench344.8Not measuredOnly GLM 4.5 measured
LMArena Text: coding14341371GLM 4.5
LMArena Text: software and IT14401373GLM 4.5
LMArena WebDev: HTMLNot measured1306Only MiniMax M2 measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
AA Intelligence Index12.818.6MiniMax M2
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
τ²-Bench Telecom43.0%86.8%MiniMax M2
Vending-Bench 2Not measured$161Only MiniMax M2 measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
GPQA Diamond72.2%Not measuredOnly GLM 4.5 measured
GPQA Diamond (Artificial Analysis run)78.2%77.7%GLM 4.5
Humanity's Last Exam (Artificial Analysis run)13.0%13.7%MiniMax M2
LMArena Text: hard prompts14291357GLM 4.5
LMArena Text: expert14331338GLM 4.5
LMArena Text: hard prompts in English14291376GLM 4.5
Kagi LLM Benchmark57.9%57.8%GLM 4.5
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
AIME86.7%Not measuredOnly GLM 4.5 measured
MATH 500 (Vals AI)94.0%Not measuredOnly GLM 4.5 measured
MGSM (Vals AI)90.8%Not measuredOnly GLM 4.5 measured
AA Math Index73.778.3MiniMax M2
AIME 2025 (Artificial Analysis run)73.7%78.3%MiniMax M2
LMArena Text: math14271351GLM 4.5
LMArena Text: mathematical work14301368GLM 4.5
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
MMLU Pro81.2%Not measuredOnly GLM 4.5 measured
LegalBench (Vals AI)75.6%Not measuredOnly GLM 4.5 measured
CorpFin (Vals AI)61.0%Not measuredOnly GLM 4.5 measured
TaxEval (Vals AI)72.4%Not measuredOnly GLM 4.5 measured
MedQA (Vals AI)90.0%Not measuredOnly GLM 4.5 measured
MMLU Pro (Artificial Analysis run)83.5%82.0%GLM 4.5
LMArena Text: science14441348GLM 4.5
LMArena Text: medicine and healthcare14551367GLM 4.5
LMArena Text: legal and government14381349GLM 4.5
LMArena Text: business and finance14201336GLM 4.5
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
Design Arena: websites11691143GLM 4.5
Design Arena: UI components11411137GLM 4.5
Design Arena: game dev11441118GLM 4.5
Design Arena: data viz11591140GLM 4.5
Design Arena: 3D11701098GLM 4.5
Design Arena: all code categories11651135GLM 4.5
Design Arena: SVG10961100MiniMax M2
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index152
General benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
IFBench44.1%72.3%MiniMax M2
Long context reasoning (AA-LCR)52.7%64.3%MiniMax M2
Creative writing (Lech Mazur)73.4%Not measuredOnly GLM 4.5 measured
LMArena Text14301340GLM 4.5
LMArena Text: instruction following14041329GLM 4.5
LMArena Text: creative writing13951286GLM 4.5
LMArena Text: English14371364GLM 4.5
LMArena Text: non-English14171313GLM 4.5
LMArena Text: Chinese14651366GLM 4.5
LMArena Text: German14071357GLM 4.5
LMArena Text: Japanese1415Not measuredOnly GLM 4.5 measured
LMArena Text: Korean1380Not measuredOnly GLM 4.5 measured
LMArena Text: French14181336GLM 4.5
LMArena Text: Spanish14541326GLM 4.5
LMArena Text: Russian14131330GLM 4.5
LMArena Text: Polish14221312GLM 4.5
LMArena Text: multi-turn14151361GLM 4.5
LMArena Text: longer queries14121331GLM 4.5
LMArena Text: writing and language14031295GLM 4.5
LMArena Text: entertainment and media14041298GLM 4.5
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5 and MiniMax M2
BenchmarkGLM 4.5MiniMax M2Leader
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

GLM 4.5$0.0017Fits in one request
MiniMax M2$0.0008Fits in one request

MiniMax M2 costs less

Repository review

50K input + 3K output tokens

GLM 4.5$0.037Fits in one request
MiniMax M2$0.016Fits in one request

MiniMax M2 costs less

Agent loop

200K input + 10K output tokens

GLM 4.5$0.142Exceeds the context window
MiniMax M2$0.061Exceeds the context window

MiniMax M2 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 GLM 4.5 and MiniMax M2
SpecificationZ.ai GLM 4.5MiniMax M2
MakerZ.aiMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025October 23, 2025
Context window131K205K
Input $/Mtok$0.60$0.255
Output $/Mtok$2.20$1.02
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.702
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 better than MiniMax M2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.5 or MiniMax M2?

GLM 4.5 costs $0.60 per million input tokens and $2.20 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Cost per solved task is known for MiniMax M2 only.

Which has the bigger context window, GLM 4.5 or MiniMax M2?

MiniMax M2, with 205K tokens against 131K.

How many benchmarks is the GLM 4.5 vs MiniMax M2 comparison based on?

46 benchmarks have a result for both models as of October 22, 2026. GLM 4.5's coding index rests on 0 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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