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GPT-4.1 Nano vs MiniMax M2.7

MiniMax M2.7 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 22.8 to 7.8, and GPT-4.1 Nano costs 3.0x less per output token ($0.40 vs $1.20 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace GPT-4.1 Nano Replace MiniMax M2.7
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
47
vs boards won of 47 shared

GPT-4.1 Nano or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.

Pick GPT-4.1 Nano for output tokens 3.0x cheaper ($0.40 vs $1.20 per million) and a larger context window (1.05M against 205K tokens).

Model AGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
47
GPT-4.1 Nano only
24
MiniMax M2.7 only
27
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-4.1 Nano not benchmarked, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Agentic work, 67.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-4.1 Nano 17.3% against MiniMax M2.7 84.8%, 67.5 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against MiniMax M2.7 $1.20 per million output tokens, 3.0x apart.
Context window
GPT-4.1 Nano takes 1.05M 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-4.1 NanoBarsMiniMax M2.7Ties
Coding06
Intelligence02
Agentic work01
Reasoning06
Math03
Knowledge08
Web design06
General015
All shared boards047
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding Index11.152.6MiniMax M2.7
LiveCodeBench (Vals AI)42.7%79.9%MiniMax M2.7
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
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)32.6%Not measuredOnly GPT-4.1 Nano measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdML19.0%37.0%MiniMax M2.7
ALE-BenchNot measured599.3Only MiniMax M2.7 measured
LMArena Text: coding13061454MiniMax M2.7
LMArena Text: software and IT13051446MiniMax M2.7
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
AA Intelligence Index7.822.8MiniMax M2.7
Epoch Capabilities Index129.5145.8MiniMax M2.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 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 Telecom17.3%84.8%MiniMax M2.7
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
GPQA Diamond50.8%86.6%MiniMax M2.7
MMMU Pro (Vals AI)55.0%Not measuredOnly GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)51.2%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)3.8%29.6%MiniMax M2.7
GPQA Diamond (Epoch AI run)48.9%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI0.0%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Nano measured
Chess puzzles0.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: hard prompts12861422MiniMax M2.7
LMArena Text: expert12711443MiniMax M2.7
LMArena Text: hard prompts in English12931441MiniMax M2.7
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
AIME26.5%91.0%MiniMax M2.7
MATH 500 (Vals AI)80.2%Not measuredOnly GPT-4.1 Nano measured
MGSM (Vals AI)69.3%Not measuredOnly GPT-4.1 Nano measured
AA Math Index24.0Not measuredOnly GPT-4.1 Nano measured
AIME 2025 (Artificial Analysis run)24.0%Not measuredOnly GPT-4.1 Nano measured
OTIS Mock AIME28.9%Not measuredOnly GPT-4.1 Nano measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math12741421MiniMax M2.7
LMArena Text: mathematical work12741437MiniMax M2.7
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index08
Knowledge benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
MMLU Pro63.5%80.4%MiniMax M2.7
LegalBench (Vals AI)61.1%84.0%MiniMax M2.7
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)42.1%61.2%MiniMax M2.7
TaxEval (Vals AI)60.8%66.6%MiniMax M2.7
MortgageTax (Vals AI)52.8%Not measuredOnly GPT-4.1 Nano measured
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
MMLU Pro (Artificial Analysis run)65.7%Not measuredOnly GPT-4.1 Nano measured
SimpleQA Verified6.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: science12971416MiniMax M2.7
LMArena Text: medicine and healthcare12761409MiniMax M2.7
LMArena Text: legal and government13001403MiniMax M2.7
LMArena Text: business and finance12671407MiniMax M2.7
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
Design Arena: websites9731242MiniMax M2.7
Design Arena: UI components9131207MiniMax M2.7
Design Arena: game dev9701209MiniMax M2.7
Design Arena: data viz8911233MiniMax M2.7
Design Arena: 3D9241194MiniMax M2.7
Design Arena: all code categories9621233MiniMax M2.7
Design Arena: SVGNot measured1137Only MiniMax M2.7 measured
Design Arena: ASCII artNot measured1136Only MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench32.0%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)20.3%78.3%MiniMax M2.7
DTBench52.5%Not measuredOnly GPT-4.1 Nano measured
LMCA5.5%Not measuredOnly GPT-4.1 Nano measured
Fiction.LiveBench25.0%Not measuredOnly GPT-4.1 Nano measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text12851405MiniMax M2.7
LMArena Text: instruction following12661405MiniMax M2.7
LMArena Text: creative writing12601354MiniMax M2.7
LMArena Vision1063Not measuredOnly GPT-4.1 Nano measured
LMArena Text: English13031426MiniMax M2.7
LMArena Text: non-English12601382MiniMax M2.7
LMArena Text: Chinese12701442MiniMax M2.7
LMArena Text: German12881398MiniMax M2.7
LMArena Text: Japanese11981260MiniMax M2.7
LMArena Text: KoreanNot measured1314Only MiniMax M2.7 measured
LMArena Text: FrenchNot measured1424Only MiniMax M2.7 measured
LMArena Text: SpanishNot measured1402Only MiniMax M2.7 measured
LMArena Text: Russian12611383MiniMax M2.7
LMArena Text: PolishNot measured1387Only MiniMax M2.7 measured
LMArena Text: multi-turn12771412MiniMax M2.7
LMArena Text: longer queries12831418MiniMax M2.7
LMArena Text: writing and language12611376MiniMax M2.7
LMArena Text: entertainment and media12431360MiniMax M2.7
LMArena Vision: English1101Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Nano and MiniMax M2.7
BenchmarkGPT-4.1 NanoMiniMax 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-4.1 Nano$0.0003Fits in one request
MiniMax M2.7$0.0009Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
MiniMax M2.7$0.019Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
MiniMax M2.7$0.072Exceeds the context window

GPT-4.1 Nano 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-4.1 Nano and MiniMax M2.7
SpecificationOpenAI GPT-4.1 NanoMiniMax M2.7
MakerOpenAIMiniMax
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025March 18, 2026
Context window1.05M205K
Input $/Mtok$0.10$0.30
Output $/Mtok$0.40$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it03
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 3.0x cheaper ($0.40 vs $1.20 per million) and a larger context window (1.05M against 205K tokens).

Which is cheaper, GPT-4.1 Nano or MiniMax M2.7?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, GPT-4.1 Nano or MiniMax M2.7?

GPT-4.1 Nano, with 1.05M tokens against 205K.

How many benchmarks is the GPT-4.1 Nano vs MiniMax M2.7 comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Nano's coding index rests on 0 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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