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GLM 5.3 Flash vs MiniMax M2.1

GLM 5.3 Flash leads MiniMax M2.1 on the Artificial Analysis Intelligence Index, 41.8 to 20.9, and GLM 5.3 Flash costs 2.4x less per output token ($0.50 vs $1.20 per million). Updated October 22, 2026; 19 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace MiniMax M2.1
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
16
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
3
vs boards won of 19 shared

GLM 5.3 Flash or MiniMax M2.1: which to pick

Only GLM 5.3 Flash has a coding score, 57.7 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 LiveCodeBench (Vals AI) or ALE-Bench, where it leads.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BMiniMax M2.1MiniMaxNot benchmarked1 independent benchmark$0.59 per solved task
Shared results
19
GLM 5.3 Flash only
83
MiniMax M2.1 only
15
Like-for-like categories
6 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 5.3 Flash 57.7 from 6 benchmarks, MiniMax M2.1 not benchmarked.
Widest category
Intelligence, 20.9 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: GLM 5.3 Flash 41.8 against MiniMax M2.1 20.9, 20.9 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against MiniMax M2.1 $1.20 per million output tokens, 2.4x apart.
Context window
GLM 5.3 Flash takes 1.05M 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
CategoryGLM 5.3 FlashBarsMiniMax M2.1Ties
Coding12
Intelligence10
Reasoning30
Knowledge21
Web design70
General20
All shared boards163
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
Coding benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
LiveBench coding80.6%Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev1607Not measuredOnly GLM 5.3 Flash measured
AA Coding Index71.5Not measuredOnly GLM 5.3 Flash measured
LiveCodeBench (Vals AI)80.5%81.8%MiniMax M2.1
SWE-bench Verified (Vals AI)92.0%74.8%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)37.4%Not measuredOnly GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)30.8%Not measuredOnly GLM 5.3 Flash measured
Code migration (Vals AI)20.5%Not measuredOnly GLM 5.3 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.3 Flash measured
IOI (Vals AI)52.5%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)62.9%Not measuredOnly GLM 5.3 Flash measured
Vibe Code Bench 1-100 (Vals AI)16.0%Not measuredOnly GLM 5.3 Flash measured
SkillsBench (Vals AI)40.2%Not measuredOnly GLM 5.3 Flash measured
CyberBench (Vals AI)67.9%Not measuredOnly GLM 5.3 Flash measured
LiveCodeBench (Artificial Analysis run)Not measured81.0%Only MiniMax M2.1 measured
SciCode51.6%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only MiniMax M2.1 measured
Terminal-BenchNot measured36.6%Only MiniMax M2.1 measured
FrontierCode31.8%Not measuredOnly GLM 5.3 Flash measured
FrontierSWE18.1%Not measuredOnly GLM 5.3 Flash measured
ALE-Bench303.6623.8MiniMax M2.1
LMArena Text: coding1507Not measuredOnly GLM 5.3 Flash measured
LMArena Text: software and IT1500Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev: React1624Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev: HTML1577Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev: from an image1578Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
AA Intelligence Index41.820.9GLM 5.3 Flash
Epoch Capabilities Index153.1Not measuredOnly GLM 5.3 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Agentic work benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
AA Agentic Index50.9Not measuredOnly GLM 5.3 Flash measured
LiveBench research70.1%Not measuredOnly GLM 5.3 Flash measured
LiveBench browser84.0%Not measuredOnly GLM 5.3 Flash measured
LiveBench long agentic28.4%Not measuredOnly GLM 5.3 Flash measured
SREBench (Vals AI)0.8%Not measuredOnly GLM 5.3 Flash measured
Finance Agent (Vals AI)57.9%Not measuredOnly GLM 5.3 Flash measured
Tax Agent Bench (Vals AI)31.6%Not measuredOnly GLM 5.3 Flash measured
Legal Research Bench (Vals AI)45.2%Not measuredOnly GLM 5.3 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)10.4%Not measuredOnly GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)55.9%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench-Science (Vals AI)2.9%Not measuredOnly GLM 5.3 Flash measured
τ²-Bench TelecomNot measured85.4%Only MiniMax M2.1 measured
APEX-Agents52.8%Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
GPQA Diamond86.4%78.5%GLM 5.3 Flash
LiveBench reasoning77.6%Not measuredOnly GLM 5.3 Flash measured
MMMU Pro (Vals AI)86.0%Not measuredOnly GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)91.2%83.0%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)39.9%23.2%GLM 5.3 Flash
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly GLM 5.3 Flash measured
ARC-AGI91.0%Not measuredOnly GLM 5.3 Flash measured
ARC-AGI-265.8%Not measuredOnly GLM 5.3 Flash measured
Chess puzzles21.0%Not measuredOnly GLM 5.3 Flash measured
Mystery game puzzles8.0%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: hard prompts1490Not measuredOnly GLM 5.3 Flash measured
LMArena Text: expert1511Not measuredOnly GLM 5.3 Flash measured
LMArena Text: hard prompts in English1488Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: diagrams1317Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: homework1318Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 7 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Math benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax 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
OTIS Mock AIME93.9%Not measuredOnly GLM 5.3 Flash measured
FrontierMath, tiers 1 to 355.8%Not measuredOnly GLM 5.3 Flash measured
FrontierMath, tier 417.1%Not measuredOnly GLM 5.3 Flash measured
ProofBench21.0%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: math1503Not measuredOnly GLM 5.3 Flash measured
LMArena Text: mathematical work1497Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index21
Knowledge benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
MMLU Pro86.1%87.0%MiniMax M2.1
LegalBench (Vals AI)83.9%75.5%GLM 5.3 Flash
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)75.6%66.3%GLM 5.3 Flash
MedQA (Vals AI)Not measured91.2%Only MiniMax M2.1 measured
MedCode (Vals AI)Not measured34.1%Only MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)Not measured87.5%Only MiniMax M2.1 measured
LMArena Text: science1484Not measuredOnly GLM 5.3 Flash measured
LMArena Text: medicine and healthcare1475Not measuredOnly GLM 5.3 Flash measured
LMArena Text: legal and government1473Not measuredOnly GLM 5.3 Flash measured
LMArena Text: business and finance1460Not measuredOnly GLM 5.3 Flash measured
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 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
Design Arena: websites12721201GLM 5.3 Flash
Design Arena: UI components13161220GLM 5.3 Flash
Design Arena: game dev12781134GLM 5.3 Flash
Design Arena: data viz12621206GLM 5.3 Flash
Design Arena: 3D13161164GLM 5.3 Flash
Design Arena: all code categories12821190GLM 5.3 Flash
Design Arena: SVG12851131GLM 5.3 Flash
Design Arena: ASCII art1267Not measuredOnly GLM 5.3 Flash measured
LiveBench design77.2%Not measuredOnly GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax M2.1Leader
Vals Index50.9%Not measuredOnly GLM 5.3 Flash measured
LiveBench data analysis76.4%Not measuredOnly GLM 5.3 Flash measured
MedScribe (Vals AI)88.9%80.8%GLM 5.3 Flash
IFBenchNot measured69.9%Only MiniMax M2.1 measured
Long context reasoning (AA-LCR)80.0%67.7%GLM 5.3 Flash
Surface Evolver Bench52.5%Not measuredOnly GLM 5.3 Flash measured
LMArena Text1471Not measuredOnly GLM 5.3 Flash measured
LMArena Text: instruction following1478Not measuredOnly GLM 5.3 Flash measured
LMArena Text: creative writing1441Not measuredOnly GLM 5.3 Flash measured
LMArena Vision1294Not measuredOnly GLM 5.3 Flash measured
LMArena Text: English1474Not measuredOnly GLM 5.3 Flash measured
LMArena Text: non-English1462Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Chinese1531Not measuredOnly GLM 5.3 Flash measured
LMArena Text: German1462Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Japanese1444Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Korean1436Not measuredOnly GLM 5.3 Flash measured
LMArena Text: French1491Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Spanish1475Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Russian1465Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Polish1450Not measuredOnly GLM 5.3 Flash measured
LMArena Text: multi-turn1469Not measuredOnly GLM 5.3 Flash measured
LMArena Text: longer queries1481Not measuredOnly GLM 5.3 Flash measured
LMArena Text: writing and language1455Not measuredOnly GLM 5.3 Flash measured
LMArena Text: entertainment and media1440Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: English1295Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: Chinese1363Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: reading text1299Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: humor1279Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: creative writing1270Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.3 Flash and MiniMax M2.1
BenchmarkGLM 5.3 FlashMiniMax 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

GLM 5.3 Flash$0.0004Fits in one request
MiniMax M2.1$0.0009Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Flash$0.0090Fits in one request
MiniMax M2.1$0.019Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Flash$0.035Fits in one request
MiniMax M2.1$0.072Exceeds the context window

GLM 5.3 Flash 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 5.3 Flash and MiniMax M2.1
SpecificationZ.ai GLM 5.3 FlashMiniMax M2.1
MakerZ.aiMiniMax
WeightsOpen weightsOpen weights
ReleasedAugust 26, 2026December 23, 2025
Context window1.05M205K
Input $/Mtok$0.15$0.30
Output $/Mtok$0.50$1.20
Coding index57.7Not benchmarked
Independent measurements behind it61
Cost per solved task$0.02$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Flash better than MiniMax M2.1 for coding?

Only GLM 5.3 Flash has a coding score, 57.7 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 LiveCodeBench (Vals AI) or ALE-Bench, where it leads.

Which is cheaper, GLM 5.3 Flash or MiniMax M2.1?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GLM 5.3 Flash costs $0.02 and MiniMax M2.1 $0.59.

Which has the bigger context window, GLM 5.3 Flash or MiniMax M2.1?

GLM 5.3 Flash, with 1.05M tokens against 205K.

How many benchmarks is the GLM 5.3 Flash vs MiniMax M2.1 comparison based on?

19 benchmarks have a result for both models as of October 22, 2026. GLM 5.3 Flash's coding index rests on 6 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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