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GLM 4.5 Air vs MiniMax M2.7

MiniMax M2.7 leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 22.8 to 11.1, at about the same output price ($1.20 vs $1.10 per million). Updated October 22, 2026; 42 benchmarks have a result for both.

Replace GLM 4.5 Air Replace MiniMax M2.7
GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
1
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
41
vs boards won of 42 shared

GLM 4.5 Air or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding.

Pick GLM 4.5 Air for output tokens 1.1x cheaper ($1.10 vs $1.20 per million) and work measured by LMArena Text: Japanese, where it leads.

Model AGLM 4.5 AirZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
42
GLM 4.5 Air only
7
MiniMax M2.7 only
32
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 Air not benchmarked, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Agentic work, 38.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 Air 46.5% against MiniMax M2.7 84.8%, 38.3 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against MiniMax M2.7 $1.20 per million output tokens, 1.1x apart.
Context window
GLM 4.5 Air takes 131K tokens, MiniMax M2.7 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 4.5 AirBarsMiniMax M2.7Ties
Coding03
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
Web design07
General118
All shared boards141
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding IndexNot measured52.6Only MiniMax M2.7 measured
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
LiveCodeBench (Artificial Analysis run)68.4%Not measuredOnly GLM 4.5 Air measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)20.5%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-BenchNot measured599.3Only MiniMax M2.7 measured
LMArena Text: coding13971454MiniMax M2.7
LMArena Text: software and IT14011446MiniMax M2.7
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
AA Intelligence Index11.122.8MiniMax M2.7
Epoch Capabilities IndexNot measured145.8Only MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench Telecom46.5%84.8%MiniMax M2.7
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)73.3%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)7.0%29.6%MiniMax M2.7
LMArena Text: hard prompts13791422MiniMax M2.7
LMArena Text: expert13701443MiniMax M2.7
LMArena Text: hard prompts in English13881441MiniMax M2.7
Kagi LLM Benchmark43.0%Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
AA Math Index80.7Not measuredOnly GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)80.7%Not measuredOnly GLM 4.5 Air measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math13961421MiniMax M2.7
LMArena Text: mathematical work13961437MiniMax M2.7
MathArena12.0%Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
MMLU Pro (Artificial Analysis run)81.5%Not measuredOnly GLM 4.5 Air measured
LMArena Text: science14071416MiniMax M2.7
LMArena Text: medicine and healthcare14021409MiniMax M2.7
LMArena Text: legal and government13821403MiniMax M2.7
LMArena Text: business and finance13711407MiniMax M2.7
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
Design Arena: websites11461242MiniMax M2.7
Design Arena: UI components11211207MiniMax M2.7
Design Arena: game dev10931209MiniMax M2.7
Design Arena: data viz11861233MiniMax M2.7
Design Arena: 3D11221194MiniMax M2.7
Design Arena: all code categories11371233MiniMax M2.7
Design Arena: SVG10701137MiniMax M2.7
Design Arena: ASCII artNot measured1136Only MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench37.6%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)46.7%78.3%MiniMax M2.7
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text13841405MiniMax M2.7
LMArena Text: instruction following13541405MiniMax M2.7
LMArena Text: creative writing13431354MiniMax M2.7
LMArena Text: English13971426MiniMax M2.7
LMArena Text: non-English13661382MiniMax M2.7
LMArena Text: Chinese14261442MiniMax M2.7
LMArena Text: German13771398MiniMax M2.7
LMArena Text: Japanese13481260GLM 4.5 Air
LMArena Text: Korean13081314MiniMax M2.7
LMArena Text: French14001424MiniMax M2.7
LMArena Text: Spanish13851402MiniMax M2.7
LMArena Text: Russian13731383MiniMax M2.7
LMArena Text: Polish13681387MiniMax M2.7
LMArena Text: multi-turn13711412MiniMax M2.7
LMArena Text: longer queries13661418MiniMax M2.7
LMArena Text: writing and language13541376MiniMax M2.7
LMArena Text: entertainment and media13391360MiniMax M2.7
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5 Air and MiniMax M2.7
BenchmarkGLM 4.5 AirMiniMax M2.7Leader
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 Air$0.0008Fits in one request
MiniMax M2.7$0.0009Fits in one request

GLM 4.5 Air costs less

Repository review

50K input + 3K output tokens

GLM 4.5 Air$0.013Fits in one request
MiniMax M2.7$0.019Fits in one request

GLM 4.5 Air costs less

Agent loop

200K input + 10K output tokens

GLM 4.5 Air$0.051Exceeds the context window
MiniMax M2.7$0.072Exceeds the context window

GLM 4.5 Air 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 Air and MiniMax M2.7
SpecificationZ.ai GLM 4.5 AirMiniMax M2.7
MakerZ.aiMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025March 18, 2026
Context window131K205K
Input $/Mtok$0.20$0.30
Output $/Mtok$1.10$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it03
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding. Pick GLM 4.5 Air for output tokens 1.1x cheaper ($1.10 vs $1.20 per million) and work measured by LMArena Text: Japanese, where it leads.

Which is cheaper, GLM 4.5 Air or MiniMax M2.7?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, GLM 4.5 Air or MiniMax M2.7?

MiniMax M2.7, with 205K tokens against 131K.

How many benchmarks is the GLM 4.5 Air vs MiniMax M2.7 comparison based on?

42 benchmarks have a result for both models as of October 22, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and MiniMax M2.7's on 3. Where only one model has a result, the page says so instead of naming a winner.

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