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GPT-5.2-Codex vs MiniMax M3

GPT-5.2-Codex leads MiniMax M3 on coding, 45.4 to 39.2 on the Vibe Coding Index, and MiniMax M3 costs 11.7x less per output token ($1.20 vs $14.00 per million). Updated October 22, 2026; 18 benchmarks have a result for both.

Replace GPT-5.2-Codex Replace MiniMax M3
GPT-5.2-CodexOpenAI
Coding
45.4
Overall
No data
Output $/M
$14.00
4
MiniMax M3MiniMax
Coding
39.2
Overall
51.7
Output $/M
$1.20
14
vs boards won of 18 shared

GPT-5.2-Codex or MiniMax M3: which to pick

Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 3 benchmarks against 6.

Pick MiniMax M3 for output tokens 11.7x cheaper ($1.20 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).

Model AGPT-5.2-CodexOpenAI45.4/1003 independent benchmarks$0.43 per solved taskModel BMiniMax M3MiniMax39.2/1006 independent benchmarks$0.56 per solved task
Shared results
18
GPT-5.2-Codex only
4
MiniMax M3 only
98
Like-for-like categories
5 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
GPT-5.2-Codex 45.4 from 3 benchmarks, MiniMax M3 39.2 from 6 benchmarks.
Widest category
Coding, 13.6 points apart on average over 8 shared benchmarks.
Widest single gap
Design Arena: agents building full-stack apps: GPT-5.2-Codex 993 against MiniMax M3 1197, 25.5 points apart on a 0 to 100 scale.
Output price
GPT-5.2-Codex $14.00 against MiniMax M3 $1.20 per million output tokens, 11.7x apart.
Context window
GPT-5.2-Codex takes 400K 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
CategoryGPT-5.2-CodexBarsMiniMax M3Ties
Coding26
Intelligence01
Agentic work23
Reasoning02
General02
All shared boards414
CodingLike-for-likeSix of these boards feed the Vibe Coding Index26
Coding benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
SWE-bench Verified72.8%Not measuredOnly GPT-5.2-Codex measured
SWE-bench Multilingual66.3%Not measuredOnly GPT-5.2-Codex measured
LiveBench codingNot measured70.9%Only MiniMax M3 measured
LMArena WebDev13391482MiniMax M3
AA Coding IndexNot measured58.6Only MiniMax M3 measured
LiveCodeBench (Vals AI)88.0%82.2%GPT-5.2-Codex
SWE-bench Verified (Vals AI)72.4%75.0%MiniMax M3
Terminal-Bench 4 (Vals AI)Not measured1.0%Only MiniMax M3 measured
Vibe Code Bench (Vals AI)37.9%47.6%MiniMax M3
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
SciCodeNot measured47.1%Only MiniMax M3 measured
Terminal-Bench Hard (Artificial Analysis run)37.1%42.4%MiniMax M3
Terminal-Bench66.5%Not measuredOnly GPT-5.2-Codex measured
FrontierCodeNot measured14.7%Only MiniMax M3 measured
ALE-Bench1299.9640.0GPT-5.2-Codex
LMArena Text: codingNot measured1470Only MiniMax M3 measured
LMArena Text: software and ITNot measured1466Only MiniMax M3 measured
LMArena WebDev: React13291478MiniMax M3
LMArena WebDev: HTML13481455MiniMax M3
LMArena WebDev: from an imageNot measured1470Only MiniMax M3 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
AA Intelligence Index28.529.2MiniMax M3
Epoch Capabilities IndexNot measured146.9Only MiniMax M3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index23
Agentic work benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
AA Agentic IndexNot measured29.5Only MiniMax M3 measured
Design Arena: agents building web apps10511200MiniMax M3
Design Arena: agents building full-stack apps9931197MiniMax M3
Design Arena: agents building mobile apps10901169MiniMax M3
Design Arena: agents building Android apps11761159GPT-5.2-Codex
Design Arena: agents building Godot games1142Not measuredOnly GPT-5.2-Codex 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 Telecom92.1%88.9%GPT-5.2-Codex
APEX-AgentsNot measured37.7%Only MiniMax M3 measured
OSWorld 2.0Not measured4.6%Only MiniMax M3 measured
Vending-Bench 2Not measured$2,158Only MiniMax M3 measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
GPQA DiamondNot measured92.7%Only MiniMax M3 measured
LiveBench reasoningNot measured74.5%Only MiniMax M3 measured
MMMU Pro (Vals AI)Not measured81.2%Only MiniMax M3 measured
GPQA Diamond (Artificial Analysis run)89.9%92.9%MiniMax M3
Humanity's Last Exam (Artificial Analysis run)35.7%39.0%MiniMax M3
GPQA Diamond (Epoch AI run)Not measured90.9%Only MiniMax M3 measured
SimpleBenchNot measured45.8%Only MiniMax M3 measured
Chess puzzlesNot measured13.0%Only MiniMax M3 measured
Mystery game puzzlesNot measured8.0%Only MiniMax M3 measured
LMArena Text: hard promptsNot measured1447Only MiniMax M3 measured
LMArena Text: expertNot measured1461Only MiniMax M3 measured
LMArena Text: hard prompts in EnglishNot measured1455Only MiniMax M3 measured
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
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
OTIS Mock AIMENot measured71.1%Only MiniMax M3 measured
ProofBenchNot measured18.0%Only MiniMax M3 measured
LMArena Text: mathNot measured1429Only MiniMax M3 measured
LMArena Text: mathematical workNot measured1448Only MiniMax M3 measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Knowledge benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
MMLU ProNot measured84.2%Only MiniMax M3 measured
LegalBench (Vals AI)Not measured85.4%Only MiniMax M3 measured
CorpFin (Vals AI)Not measured68.1%Only MiniMax M3 measured
TaxEval (Vals AI)Not measured72.7%Only MiniMax M3 measured
MortgageTax (Vals AI)Not measured68.4%Only MiniMax M3 measured
MedCode (Vals AI)Not measured46.3%Only MiniMax M3 measured
LMArena Text: scienceNot measured1452Only MiniMax M3 measured
LMArena Text: medicine and healthcareNot measured1441Only MiniMax M3 measured
LMArena Text: legal and governmentNot measured1437Only MiniMax M3 measured
LMArena Text: business and financeNot measured1434Only MiniMax M3 measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax M3Leader
Design Arena: websitesNot measured1257Only MiniMax M3 measured
Design Arena: UI componentsNot measured1242Only MiniMax M3 measured
Design Arena: game devNot measured1210Only MiniMax M3 measured
Design Arena: data vizNot measured1236Only MiniMax M3 measured
Design Arena: 3DNot measured1208Only MiniMax M3 measured
Design Arena: all code categoriesNot measured1247Only MiniMax M3 measured
Design Arena: SVGNot measured1161Only MiniMax M3 measured
Design Arena: ASCII artNot measured1161Only MiniMax M3 measured
LiveBench designNot measured66.2%Only MiniMax M3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax 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)Not measured87.3%Only MiniMax M3 measured
Vals Multimodal IndexNot measured60.0%Only MiniMax M3 measured
IFBench77.6%82.9%MiniMax M3
Long context reasoning (AA-LCR)82.3%83.0%MiniMax M3
DTBenchNot measured78.9%Only MiniMax M3 measured
LMCANot measured33.7%Only MiniMax M3 measured
Surface Evolver BenchNot measured55.0%Only MiniMax M3 measured
LMArena TextNot measured1433Only MiniMax M3 measured
LMArena Text: instruction followingNot measured1433Only MiniMax M3 measured
LMArena Text: creative writingNot measured1404Only MiniMax M3 measured
LMArena VisionNot measured1251Only MiniMax M3 measured
LMArena Text: EnglishNot measured1443Only MiniMax M3 measured
LMArena Text: non-EnglishNot measured1420Only MiniMax M3 measured
LMArena Text: ChineseNot measured1466Only MiniMax M3 measured
LMArena Text: GermanNot measured1428Only MiniMax M3 measured
LMArena Text: JapaneseNot measured1380Only MiniMax M3 measured
LMArena Text: KoreanNot measured1373Only MiniMax M3 measured
LMArena Text: FrenchNot measured1444Only MiniMax M3 measured
LMArena Text: SpanishNot measured1433Only MiniMax M3 measured
LMArena Text: RussianNot measured1426Only MiniMax M3 measured
LMArena Text: PolishNot measured1423Only MiniMax M3 measured
LMArena Text: multi-turnNot measured1443Only MiniMax M3 measured
LMArena Text: longer queriesNot measured1446Only MiniMax M3 measured
LMArena Text: writing and languageNot measured1419Only MiniMax M3 measured
LMArena Text: entertainment and mediaNot measured1403Only MiniMax M3 measured
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 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.2-Codex and MiniMax M3
BenchmarkGPT-5.2-CodexMiniMax 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

GPT-5.2-Codex$0.0088Fits in one request
MiniMax M3$0.0009Fits in one request

MiniMax M3 costs less

Repository review

50K input + 3K output tokens

GPT-5.2-Codex$0.130Fits in one request
MiniMax M3$0.019Fits in one request

MiniMax M3 costs less

Agent loop

200K input + 10K output tokens

GPT-5.2-Codex$0.490Fits in one request
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 GPT-5.2-Codex and MiniMax M3
SpecificationOpenAI GPT-5.2-CodexMiniMax M3
MakerOpenAIMiniMax
WeightsNo public weights listedOpen weights
ReleasedJanuary 14, 2026May 31, 2026
Context window400K1.05M
Input $/Mtok$1.75$0.30
Output $/Mtok$14.00$1.20
Coding index45.439.2
Independent measurements behind it36
Cost per solved task$0.43$0.56
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.2-Codex better than MiniMax M3 for coding?

Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 3 benchmarks against 6. Pick MiniMax M3 for output tokens 11.7x cheaper ($1.20 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).

Which is cheaper, GPT-5.2-Codex or MiniMax M3?

GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GPT-5.2-Codex costs $0.43 and MiniMax M3 $0.56.

Which has the bigger context window, GPT-5.2-Codex or MiniMax M3?

MiniMax M3, with 1.05M tokens against 400K.

How many benchmarks is the GPT-5.2-Codex vs MiniMax M3 comparison based on?

18 benchmarks have a result for both models as of October 22, 2026. GPT-5.2-Codex's coding index rests on 3 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/gpt-5-2-codex-vs-minimax-minimax-m3">LLMBenchmark.ai, GPT-5.2-Codex vs MiniMax M3</a></p>