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GPT-5.2 vs MiniMax M2.7

GPT-5.2 leads MiniMax M2.7 on coding, 55.9 to 36.2 on the Vibe Coding Index, and MiniMax M2.7 costs 11.7x less per output token ($1.20 vs $14.00 per million). Updated October 22, 2026; 62 benchmarks have a result for both.

Replace GPT-5.2 Replace MiniMax M2.7
GPT-5.2OpenAI
Coding
55.9
Overall
60.7
Output $/M
$14.00
48
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
13
vs boards won of 62 shared, 1 tied

GPT-5.2 or MiniMax M2.7: which to pick

Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 36.2 for MiniMax M2.7.

Pick MiniMax M2.7 for output tokens 11.7x cheaper ($1.20 vs $14.00 per million) and a lower cost per solved task ($0.64 against $1.91).

Model AGPT-5.2OpenAI55.9/1003 independent benchmarks$1.91 per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
62
GPT-5.2 only
52
MiniMax M2.7 only
12
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
GPT-5.2 55.9 from 3 benchmarks, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Coding, 13.2 points apart on average over 11 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GPT-5.2 53.5% against MiniMax M2.7 11.9%, 41.6 points apart on a 0 to 100 scale.
Output price
GPT-5.2 $14.00 against MiniMax M2.7 $1.20 per million output tokens, 11.7x apart.
Context window
GPT-5.2 takes 400K 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
CategoryGPT-5.2BarsMiniMax M2.7Ties
Coding92
Intelligence20
Agentic work001 tie
Reasoning51
Math40
Knowledge91
Web design26
General173
All shared boards48131 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index92
Coding benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
SWE-bench Verified72.8%Not measuredOnly GPT-5.2 measured
SWE-bench Multilingual66.7%Not measuredOnly GPT-5.2 measured
LMArena WebDev14171399GPT-5.2
AA Coding IndexNot measured52.6Only MiniMax M2.7 measured
LiveCodeBench (Vals AI)85.4%79.9%GPT-5.2
SWE-bench Verified (Vals AI)75.8%73.8%GPT-5.2
Vibe Code Bench (Vals AI)53.5%11.9%GPT-5.2
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)89.4%Not measuredOnly GPT-5.2 measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)47.0%39.4%GPT-5.2
Terminal-Bench64.9%45.1%GPT-5.2
GSO-Bench27.5%Not measuredOnly GPT-5.2 measured
WeirdML72.2%37.0%GPT-5.2
ALE-Bench1293.5599.3GPT-5.2
LMArena Text: coding14421454MiniMax M2.7
LMArena Text: software and IT14341446MiniMax M2.7
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTML14271401GPT-5.2
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
AA Intelligence Index30.422.8GPT-5.2
Epoch Capabilities Index153.7145.8GPT-5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index00
Agentic work benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Design Arena: agents building web apps1086Not measuredOnly GPT-5.2 measured
Design Arena: agents building full-stack apps1043Not measuredOnly GPT-5.2 measured
Design Arena: agents building mobile apps1093Not measuredOnly GPT-5.2 measured
Design Arena: agents building Android apps1059Not measuredOnly GPT-5.2 measured
Design Arena: agents building Godot games1142Not measuredOnly GPT-5.2 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 Telecom84.8%84.8%Tie
METR time horizons75.3%Not measuredOnly GPT-5.2 measured
Remote Labor Index2.5%Not measuredOnly GPT-5.2 measured
GDPval49.7%Not measuredOnly GPT-5.2 measured
DeepResearch Bench41.1%Not measuredOnly GPT-5.2 measured
Vending-Bench 2$3,591Not measuredOnly GPT-5.2 measured
Berkeley Function Calling Leaderboard (BFCL)55.9%Not measuredOnly GPT-5.2 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
GPQA Diamond91.7%86.6%GPT-5.2
MMMU Pro (Vals AI)86.7%Not measuredOnly GPT-5.2 measured
GPQA Diamond (Artificial Analysis run)90.3%87.4%GPT-5.2
Humanity's Last Exam (Artificial Analysis run)37.7%29.6%GPT-5.2
GPQA Diamond (Epoch AI run)91.4%Not measuredOnly GPT-5.2 measured
ARC-AGI86.2%Not measuredOnly GPT-5.2 measured
ARC-AGI-252.9%Not measuredOnly GPT-5.2 measured
SimpleBench45.8%Not measuredOnly GPT-5.2 measured
Chess puzzles48.0%Not measuredOnly GPT-5.2 measured
Mystery game puzzles23.0%Not measuredOnly GPT-5.2 measured
EBR-bench23.0%Not measuredOnly GPT-5.2 measured
VPCT84.0%Not measuredOnly GPT-5.2 measured
LMArena Text: hard prompts14281422GPT-5.2
LMArena Text: expert14451443GPT-5.2
LMArena Text: hard prompts in English14311441MiniMax M2.7
LMArena Vision: diagrams1265Not measuredOnly GPT-5.2 measured
LMArena Vision: homework1276Not measuredOnly GPT-5.2 measured
Kagi LLM Benchmark73.3%Not measuredOnly GPT-5.2 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
AIME96.9%91.0%GPT-5.2
MGSM (Vals AI)94.0%Not measuredOnly GPT-5.2 measured
AA Math Index99.0Not measuredOnly GPT-5.2 measured
AIME 2025 (Artificial Analysis run)99.0%Not measuredOnly GPT-5.2 measured
OTIS Mock AIME96.1%Not measuredOnly GPT-5.2 measured
FrontierMath, tiers 1 to 367.4%Not measuredOnly GPT-5.2 measured
FrontierMath, tier 431.7%Not measuredOnly GPT-5.2 measured
ProofBench15.0%3.0%GPT-5.2
LMArena Text: math14401421GPT-5.2
LMArena Text: mathematical work14421437GPT-5.2
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index91
Knowledge benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
MMLU Pro86.2%80.4%GPT-5.2
LegalBench (Vals AI)82.8%84.0%MiniMax M2.7
CaseLaw (Vals AI)66.0%60.9%GPT-5.2
CorpFin (Vals AI)65.9%61.2%GPT-5.2
TaxEval (Vals AI)75.8%66.6%GPT-5.2
MortgageTax (Vals AI)67.1%Not measuredOnly GPT-5.2 measured
MedQA (Vals AI)94.1%Not measuredOnly GPT-5.2 measured
MedCode (Vals AI)49.8%34.4%GPT-5.2
MMLU Pro (Artificial Analysis run)87.4%Not measuredOnly GPT-5.2 measured
SimpleQA Verified37.1%Not measuredOnly GPT-5.2 measured
LMArena Text: science14251416GPT-5.2
LMArena Text: medicine and healthcare14251409GPT-5.2
LMArena Text: legal and government14271403GPT-5.2
LMArena Text: business and finance14141407GPT-5.2
FACTS Benchmark Suite48.5%Not measuredOnly GPT-5.2 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index26
Web design benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
Design Arena: websites11951243MiniMax M2.7
Design Arena: UI components11901210MiniMax M2.7
Design Arena: game dev11951209MiniMax M2.7
Design Arena: data viz12021233MiniMax M2.7
Design Arena: 3D10791195MiniMax M2.7
Design Arena: all code categories11701233MiniMax M2.7
Design Arena: SVG11391137GPT-5.2
Design Arena: ASCII art11521136GPT-5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index173
General benchmarks for GPT-5.2 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax M2.7Leader
SAGE (Vals AI)49.3%Not measuredOnly GPT-5.2 measured
MedScribe (Vals AI)84.4%79.9%GPT-5.2
IFBench75.4%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)82.7%78.3%GPT-5.2
DTBench90.9%Not measuredOnly GPT-5.2 measured
LMCA43.9%Not measuredOnly GPT-5.2 measured
CL-bench18.2%Not measuredOnly GPT-5.2 measured
Furniture assembly38.3%Not measuredOnly GPT-5.2 measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text14161405GPT-5.2
LMArena Text: instruction following14091405GPT-5.2
LMArena Text: creative writing13761354GPT-5.2
LMArena Vision1246Not measuredOnly GPT-5.2 measured
LMArena Text: English14221426MiniMax M2.7
LMArena Text: non-English14051382GPT-5.2
LMArena Text: Chinese14471442GPT-5.2
LMArena Text: German14441398GPT-5.2
LMArena Text: Japanese14201260GPT-5.2
LMArena Text: Korean13741314GPT-5.2
LMArena Text: French14541424GPT-5.2
LMArena Text: Spanish14131402GPT-5.2
LMArena Text: Russian14151383GPT-5.2
LMArena Text: Polish14261387GPT-5.2
LMArena Text: multi-turn14191412GPT-5.2
LMArena Text: longer queries14131418MiniMax M2.7
LMArena Text: writing and language13921376GPT-5.2
LMArena Text: entertainment and media13781360GPT-5.2
LMArena Vision: English1243Not measuredOnly GPT-5.2 measured
LMArena Vision: Chinese1305Not measuredOnly GPT-5.2 measured
LMArena Vision: reading text1257Not measuredOnly GPT-5.2 measured
LMArena Vision: humor1227Not measuredOnly GPT-5.2 measured
LMArena Vision: captioning1267Not measuredOnly GPT-5.2 measured
LMArena Vision: recognizing things1232Not measuredOnly GPT-5.2 measured
LMArena Vision: creative writing1225Not measuredOnly GPT-5.2 measured
LMArena Document1405Not measuredOnly GPT-5.2 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 and MiniMax M2.7
BenchmarkGPT-5.2MiniMax 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

GPT-5.2$0.0088Fits in one request
MiniMax M2.7$0.0009Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

GPT-5.2$0.130Fits in one request
MiniMax M2.7$0.019Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

GPT-5.2$0.490Fits in one request
MiniMax M2.7$0.072Exceeds the context window

MiniMax M2.7 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 and MiniMax M2.7
SpecificationOpenAI GPT-5.2MiniMax M2.7
MakerOpenAIMiniMax
WeightsNo public weights listedOpen weights
ReleasedDecember 10, 2025March 18, 2026
Context window400K205K
Input $/Mtok$1.75$0.30
Output $/Mtok$14.00$1.20
Coding index55.936.2
Independent measurements behind it33
Cost per solved task$1.91$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.2 better than MiniMax M2.7 for coding?

Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 36.2 for MiniMax M2.7. Pick MiniMax M2.7 for output tokens 11.7x cheaper ($1.20 vs $14.00 per million) and a lower cost per solved task ($0.64 against $1.91).

Which is cheaper, GPT-5.2 or MiniMax M2.7?

GPT-5.2 costs $1.75 per million input tokens and $14.00 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GPT-5.2 costs $1.91 and MiniMax M2.7 $0.64.

Which has the bigger context window, GPT-5.2 or MiniMax M2.7?

GPT-5.2, with 400K tokens against 205K.

How many benchmarks is the GPT-5.2 vs MiniMax M2.7 comparison based on?

62 benchmarks have a result for both models as of October 22, 2026. GPT-5.2's coding index rests on 3 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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<iframe src="https://llmbenchmark.ai/embed/compare/gpt-5-2-vs-minimax-minimax-m2-7" title="GPT-5.2 vs MiniMax M2.7, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-5-2-vs-minimax-minimax-m2-7">LLMBenchmark.ai, GPT-5.2 vs MiniMax M2.7</a></p>