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GLM 5.1 vs MiniMax M2

GLM 5.1 leads MiniMax M2 on the Artificial Analysis Intelligence Index, 26.1 to 18.6, and MiniMax M2 costs 4.3x less per output token ($1.02 vs $4.40 per million). Updated October 22, 2026; 43 benchmarks have a result for both.

Replace GLM 5.1 Replace MiniMax M2
GLM 5.1Z.ai
Coding
49.2
Overall
57.5
Output $/M
$4.40
43
MiniMax M2MiniMax
Coding
No data
Overall
No data
Output $/M
$1.02
0
vs boards won of 43 shared

GLM 5.1 or MiniMax M2: which to pick

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding.

Pick MiniMax M2 for output tokens 4.3x cheaper ($1.02 vs $4.40 per million).

Model AGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved taskModel BMiniMax M2MiniMaxNot benchmarked1 independent benchmark$0.702 per solved task
Shared results
43
GLM 5.1 only
46
MiniMax M2 only
7
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 5.1 49.2 from 3 benchmarks, MiniMax M2 not benchmarked.
Widest category
Coding, 23.8 points apart on average over 5 shared benchmarks.
Widest single gap
Vending-Bench 2: GLM 5.1 $5,634 against MiniMax M2 $161, 34.2 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against MiniMax M2 $1.02 per million output tokens, 4.3x apart.
Context window
Both take 205K tokens.

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 5.1BarsMiniMax M2Ties
Coding50
Intelligence10
Agentic work20
Reasoning50
Math20
Knowledge40
Web design70
General170
All shared boards430
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
SWE-bench VerifiedNot measured61.0%Only MiniMax M2 measured
LMArena WebDev15081297GLM 5.1
AA Coding Index55.8Not measuredOnly GLM 5.1 measured
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly GLM 5.1 measured
Vibe Code Bench (Vals AI)31.5%Not measuredOnly GLM 5.1 measured
Code migration (Vals AI)25.8%Not measuredOnly GLM 5.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%Not measuredOnly GLM 5.1 measured
LiveCodeBench (Artificial Analysis run)Not measured82.6%Only MiniMax M2 measured
SciCode44.8%Not measuredOnly GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%25.8%GLM 5.1
Terminal-BenchNot measured30.0%Only MiniMax M2 measured
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1Not measuredOnly GLM 5.1 measured
LMArena Text: coding14851371GLM 5.1
LMArena Text: software and IT14841373GLM 5.1
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML15081306GLM 5.1
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
AA Intelligence Index26.118.6GLM 5.1
Epoch Capabilities Index149.8Not measuredOnly GLM 5.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
AA Agentic Index23.9Not measuredOnly GLM 5.1 measured
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1162Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1182Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1120Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1163Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%Not measuredOnly GLM 5.1 measured
Legal Research Bench (Vals AI)27.9%Not measuredOnly GLM 5.1 measured
τ²-Bench Telecom97.7%86.8%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634$161GLM 5.1
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%77.7%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%13.7%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%Not measuredOnly GLM 5.1 measured
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts14731357GLM 5.1
LMArena Text: expert14781338GLM 5.1
LMArena Text: hard prompts in English14821376GLM 5.1
Kagi LLM BenchmarkNot measured57.8%Only MiniMax M2 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
AIME91.9%Not measuredOnly GLM 5.1 measured
AA Math IndexNot measured78.3Only MiniMax M2 measured
AIME 2025 (Artificial Analysis run)Not measured78.3%Only MiniMax M2 measured
OTIS Mock AIME93.3%Not measuredOnly GLM 5.1 measured
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math14731351GLM 5.1
LMArena Text: mathematical work14701368GLM 5.1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
MMLU Pro86.9%Not measuredOnly GLM 5.1 measured
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%Not measuredOnly GLM 5.1 measured
TaxEval (Vals AI)71.2%Not measuredOnly GLM 5.1 measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
MMLU Pro (Artificial Analysis run)Not measured82.0%Only MiniMax M2 measured
SimpleQA Verified34.0%Not measuredOnly GLM 5.1 measured
LMArena Text: science14781348GLM 5.1
LMArena Text: medicine and healthcare14741367GLM 5.1
LMArena Text: legal and government14651349GLM 5.1
LMArena Text: business and finance14521336GLM 5.1
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
Design Arena: websites12901143GLM 5.1
Design Arena: UI components12921137GLM 5.1
Design Arena: game dev12651118GLM 5.1
Design Arena: data viz13661140GLM 5.1
Design Arena: 3D13361098GLM 5.1
Design Arena: all code categories12681135GLM 5.1
Design Arena: SVG12181100GLM 5.1
Design Arena: ASCII art1141Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
General benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax M2Leader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
MedScribe (Vals AI)72.3%Not measuredOnly GLM 5.1 measured
IFBench76.3%72.3%GLM 5.1
Long context reasoning (AA-LCR)73.7%64.3%GLM 5.1
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631340GLM 5.1
LMArena Text: instruction following14531329GLM 5.1
LMArena Text: creative writing14531286GLM 5.1
LMArena Text: English14761364GLM 5.1
LMArena Text: non-English14481313GLM 5.1
LMArena Text: Chinese15151366GLM 5.1
LMArena Text: German14671357GLM 5.1
LMArena Text: Japanese1435Not measuredOnly GLM 5.1 measured
LMArena Text: Korean1424Not measuredOnly GLM 5.1 measured
LMArena Text: French14701336GLM 5.1
LMArena Text: Spanish14681326GLM 5.1
LMArena Text: Russian14541330GLM 5.1
LMArena Text: Polish14491312GLM 5.1
LMArena Text: multi-turn14731361GLM 5.1
LMArena Text: longer queries14671331GLM 5.1
LMArena Text: writing and language14541295GLM 5.1
LMArena Text: entertainment and media14421298GLM 5.1
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.1 and MiniMax M2
BenchmarkGLM 5.1MiniMax 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 5.1$0.0036Fits in one request
MiniMax M2$0.0008Fits in one request

MiniMax M2 costs less

Repository review

50K input + 3K output tokens

GLM 5.1$0.083Fits in one request
MiniMax M2$0.016Fits in one request

MiniMax M2 costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds 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 5.1 and MiniMax M2
SpecificationZ.ai GLM 5.1MiniMax M2
MakerZ.aiMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 7, 2026October 23, 2025
Context window205K205K
Input $/Mtok$1.40$0.255
Output $/Mtok$4.40$1.02
Coding index49.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.60$0.702
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than MiniMax M2 for coding?

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding. Pick MiniMax M2 for output tokens 4.3x cheaper ($1.02 vs $4.40 per million).

Which is cheaper, GLM 5.1 or MiniMax M2?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Per solved SWE-bench Verified task, GLM 5.1 costs $0.60 and MiniMax M2 $0.702.

Which has the bigger context window, GLM 5.1 or MiniMax M2?

Neither: both take 205K tokens.

How many benchmarks is the GLM 5.1 vs MiniMax M2 comparison based on?

43 benchmarks have a result for both models as of October 22, 2026. GLM 5.1's coding index rests on 3 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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