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GLM 4.7 vs MiniMax M3

GLM 4.7 leads MiniMax M3 on coding, 55.1 to 39.2 on the Vibe Coding Index, and MiniMax M3 costs 1.8x less per output token ($1.20 vs $2.20 per million). Updated October 22, 2026; 67 benchmarks have a result for both.

Replace GLM 4.7 Replace MiniMax M3
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
18
MiniMax M3MiniMax
Coding
39.2
Overall
51.7
Output $/M
$1.20
49
vs boards won of 67 shared

GLM 4.7 or MiniMax M3: which to pick

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 2 benchmarks against 6.

Pick MiniMax M3 for output tokens 1.8x cheaper ($1.20 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BMiniMax M3MiniMax39.2/1006 independent benchmarks$0.56 per solved task
Shared results
67
GLM 4.7 only
14
MiniMax M3 only
49
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 4.7 55.1 from 2 benchmarks, MiniMax M3 39.2 from 6 benchmarks.
Widest category
Agentic work, 8.1 points apart on average over 5 shared benchmarks.
Widest single gap
CorpFin (Vals AI): GLM 4.7 46.4% against MiniMax M3 68.1%, 21.7 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against MiniMax M3 $1.20 per million output tokens, 1.8x apart.
Context window
GLM 4.7 takes 205K tokens, MiniMax M3 1.05M.

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 4.7BarsMiniMax M3Ties
Coding19
Intelligence02
Agentic work23
Reasoning27
Math13
Knowledge36
Web design17
General812
All shared boards1849
CodingLike-for-likeSix of these boards feed the Vibe Coding Index19
Coding benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
LiveBench codingNot measured70.9%Only MiniMax M3 measured
LMArena WebDev14351482MiniMax M3
AA Coding Index45.358.6MiniMax M3
LiveCodeBench (Vals AI)82.2%82.2%GLM 4.7
SWE-bench Verified (Vals AI)69.4%75.0%MiniMax M3
Terminal-Bench 4 (Vals AI)Not measured1.0%Only MiniMax M3 measured
Vibe Code Bench (Vals AI)Not measured47.6%Only MiniMax M3 measured
Code migration (Vals AI)Not measured19.9%Only MiniMax M3 measured
Terminal-Bench 2.1 (Vals AI)Not measured53.6%Only MiniMax M3 measured
SWE-bench Multimodal (Vals AI)Not measured33.3%Only MiniMax M3 measured
Vibe Code Bench 1-100 (Vals AI)Not measured9.2%Only MiniMax M3 measured
SkillsBench (Vals AI)Not measured51.5%Only MiniMax M3 measured
CyberBench (Vals AI)Not measured65.0%Only MiniMax M3 measured
LiveCodeBench (Artificial Analysis run)89.4%Not measuredOnly GLM 4.7 measured
SciCodeNot measured47.1%Only MiniMax M3 measured
Terminal-Bench Hard (Artificial Analysis run)31.8%42.4%MiniMax M3
Terminal-Bench33.4%Not measuredOnly GLM 4.7 measured
FrontierCodeNot measured14.7%Only MiniMax M3 measured
ALE-Bench399.5640.0MiniMax M3
LMArena Text: coding14541470MiniMax M3
LMArena Text: software and IT14531466MiniMax M3
LMArena WebDev: React14201478MiniMax M3
LMArena WebDev: HTML14471455MiniMax M3
LMArena WebDev: from an imageNot measured1470Only MiniMax M3 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
AA Intelligence Index22.229.2MiniMax M3
Epoch Capabilities Index143.6146.9MiniMax M3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index23
Agentic work benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
AA Agentic IndexNot measured29.5Only MiniMax M3 measured
Design Arena: agents building web appsNot measured1200Only MiniMax M3 measured
Design Arena: agents building full-stack apps10501197MiniMax M3
Design Arena: agents building mobile apps11051169MiniMax M3
Design Arena: agents building Android apps11121159MiniMax M3
Design Arena: agents building Godot games1058Not measuredOnly GLM 4.7 measured
Design Arena: agents building gamesNot measured1158Only MiniMax M3 measured
Design Arena: HTML slidesNot measured1130Only MiniMax M3 measured
Design Arena: PowerPoint slidesNot measured1181Only MiniMax M3 measured
Design Arena: spreadsheetsNot measured1028Only MiniMax M3 measured
LiveBench researchNot measured68.0%Only MiniMax M3 measured
LiveBench browserNot measured8.0%Only MiniMax M3 measured
LiveBench long agenticNot measured12.4%Only MiniMax M3 measured
Finance Agent (Vals AI)Not measured48.3%Only MiniMax M3 measured
Tax Agent Bench (Vals AI)Not measured20.6%Only MiniMax M3 measured
Legal Research Bench (Vals AI)Not measured29.8%Only MiniMax M3 measured
Excel Modeling Benchmark (Vals AI)Not measured47.8%Only MiniMax M3 measured
τ²-Bench Telecom95.9%88.9%GLM 4.7
APEX-AgentsNot measured37.7%Only MiniMax M3 measured
OSWorld 2.0Not measured4.6%Only MiniMax M3 measured
Vending-Bench 2$2,377$2,158GLM 4.7
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 19 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index27
Reasoning benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
GPQA Diamond80.0%92.7%MiniMax M3
LiveBench reasoningNot measured74.5%Only MiniMax M3 measured
MMMU Pro (Vals AI)Not measured81.2%Only MiniMax M3 measured
GPQA Diamond (Artificial Analysis run)85.9%92.9%MiniMax M3
Humanity's Last Exam (Artificial Analysis run)27.4%39.0%MiniMax M3
GPQA Diamond (Epoch AI run)83.3%90.9%MiniMax M3
SimpleBench47.7%45.8%GLM 4.7
Chess puzzles21.0%13.0%GLM 4.7
Mystery game puzzlesNot measured8.0%Only MiniMax M3 measured
LMArena Text: hard prompts14431447MiniMax M3
LMArena Text: expert14241461MiniMax M3
LMArena Text: hard prompts in English14521455MiniMax M3
LMArena Vision: diagramsNot measured1266Only MiniMax M3 measured
LMArena Vision: homeworkNot measured1268Only MiniMax M3 measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
AIME93.3%Not measuredOnly GLM 4.7 measured
MGSM (Vals AI)88.2%Not measuredOnly GLM 4.7 measured
AA Math Index95.0Not measuredOnly GLM 4.7 measured
AIME 2025 (Artificial Analysis run)95.0%Not measuredOnly GLM 4.7 measured
OTIS Mock AIME83.3%71.1%GLM 4.7
ProofBench6.0%18.0%MiniMax M3
LMArena Text: math14241429MiniMax M3
LMArena Text: mathematical work14111448MiniMax M3
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index36
Knowledge benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
MMLU Pro82.7%84.2%MiniMax M3
LegalBench (Vals AI)83.4%85.4%MiniMax M3
CaseLaw (Vals AI)54.9%Not measuredOnly GLM 4.7 measured
CorpFin (Vals AI)46.4%68.1%MiniMax M3
TaxEval (Vals AI)68.8%72.7%MiniMax M3
MortgageTax (Vals AI)Not measured68.4%Only MiniMax M3 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%46.3%MiniMax M3
MMLU Pro (Artificial Analysis run)85.6%Not measuredOnly GLM 4.7 measured
SimpleQA Verified32.2%Not measuredOnly GLM 4.7 measured
LMArena Text: science14571452GLM 4.7
LMArena Text: medicine and healthcare14691441GLM 4.7
LMArena Text: legal and government14441437GLM 4.7
LMArena Text: business and finance14291434MiniMax M3
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
Design Arena: websites12251257MiniMax M3
Design Arena: UI components11961242MiniMax M3
Design Arena: game dev11881210MiniMax M3
Design Arena: data viz11951236MiniMax M3
Design Arena: 3D11901208MiniMax M3
Design Arena: all code categories12161247MiniMax M3
Design Arena: SVG11421161MiniMax M3
Design Arena: ASCII art11651161GLM 4.7
LiveBench designNot measured66.2%Only MiniMax M3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index812
General benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
LiveBench data analysisNot measured76.2%Only MiniMax M3 measured
Public Benefits Bench (Vals AI)Not measured64.1%Only MiniMax M3 measured
SAGE (Vals AI)Not measured50.6%Only MiniMax M3 measured
MedScribe (Vals AI)68.6%87.3%MiniMax M3
Vals Multimodal IndexNot measured60.0%Only MiniMax M3 measured
IFBench67.9%82.9%MiniMax M3
Long context reasoning (AA-LCR)71.0%83.0%MiniMax M3
DTBenchNot measured78.9%Only MiniMax M3 measured
LMCANot measured33.7%Only MiniMax M3 measured
CL-bench15.9%Not measuredOnly GLM 4.7 measured
Surface Evolver BenchNot measured55.0%Only MiniMax M3 measured
CL-bench Life10.9%Not measuredOnly GLM 4.7 measured
LMArena Text14351433GLM 4.7
LMArena Text: instruction following14121433MiniMax M3
LMArena Text: creative writing14011404MiniMax M3
LMArena VisionNot measured1251Only MiniMax M3 measured
LMArena Text: English14531443GLM 4.7
LMArena Text: non-English14171420MiniMax M3
LMArena Text: Chinese14951466GLM 4.7
LMArena Text: German14261428MiniMax M3
LMArena Text: Japanese14391380GLM 4.7
LMArena Text: Korean13991373GLM 4.7
LMArena Text: French14321444MiniMax M3
LMArena Text: Spanish14341433GLM 4.7
LMArena Text: Russian14231426MiniMax M3
LMArena Text: Polish14351423GLM 4.7
LMArena Text: multi-turn14461443GLM 4.7
LMArena Text: longer queries14321446MiniMax M3
LMArena Text: writing and language14111419MiniMax M3
LMArena Text: entertainment and media14001403MiniMax M3
LMArena Vision: EnglishNot measured1263Only MiniMax M3 measured
LMArena Vision: ChineseNot measured1311Only MiniMax M3 measured
LMArena Vision: reading textNot measured1259Only MiniMax M3 measured
LMArena Vision: humorNot measured1235Only MiniMax M3 measured
LMArena Vision: recognizing thingsNot measured1197Only MiniMax M3 measured
LMArena Vision: creative writingNot measured1234Only MiniMax M3 measured
LMArena DocumentNot measured1435Only MiniMax M3 measured
Neither model has a result on the other 9 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 and MiniMax M3
BenchmarkGLM 4.7MiniMax M3Leader
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 4.7$0.0017Fits in one request
MiniMax M3$0.0009Fits in one request

MiniMax M3 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
MiniMax M3$0.019Fits in one request

MiniMax M3 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
MiniMax M3$0.072Fits in one request

MiniMax M3 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 4.7 and MiniMax M3
SpecificationZ.ai GLM 4.7MiniMax M3
MakerZ.aiMiniMax
WeightsOpen weightsOpen weights
ReleasedDecember 22, 2025May 31, 2026
Context window205K1.05M
Input $/Mtok$0.60$0.30
Output $/Mtok$2.20$1.20
Coding index55.139.2
Independent measurements behind it26
Cost per solved task$0.29$0.56
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than MiniMax M3 for coding?

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 2 benchmarks against 6. Pick MiniMax M3 for output tokens 1.8x cheaper ($1.20 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).

Which is cheaper, GLM 4.7 or MiniMax M3?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GLM 4.7 costs $0.29 and MiniMax M3 $0.56.

Which has the bigger context window, GLM 4.7 or MiniMax M3?

MiniMax M3, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.7 vs MiniMax M3 comparison based on?

67 benchmarks have a result for both models as of October 22, 2026. GLM 4.7's coding index rests on 2 independent benchmarks and MiniMax M3's on 6. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-4-7-vs-minimax-minimax-m3">LLMBenchmark.ai, GLM 4.7 vs MiniMax M3</a></p>