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GPT-4o (2024-08-06) vs MiniMax M2.5

MiniMax M2.5 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 22.8 to 7.7, and MiniMax M2.5 costs 8.3x less per output token ($1.20 vs $10.00 per million). Updated October 23, 2026; 40 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace MiniMax M2.5
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
3
MiniMax M2.5MiniMax
Coding
37.2
Overall
37.3
Output $/M
$1.20
37
vs boards won of 40 shared

GPT-4o (2024-08-06) or MiniMax M2.5: which to pick

Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding.

Pick GPT-4o (2024-08-06) for work measured by LegalBench (Vals AI) or TaxEval (Vals AI), where it leads.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M2.5MiniMax37.2/1003 independent benchmarks$0.62 per solved task
Shared results
40
GPT-4o (2024-08-06) only
18
MiniMax M2.5 only
31
Like-for-like categories
7 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-4o (2024-08-06) not benchmarked, MiniMax M2.5 37.2 from 3 benchmarks.
Widest category
Agentic work, 66.4 points apart on average over 1 shared benchmark.
Widest single gap
AIME: GPT-4o (2024-08-06) 14.0% against MiniMax M2.5 88.8%, 74.8 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against MiniMax M2.5 $1.20 per million output tokens, 8.3x apart.
Context window
GPT-4o (2024-08-06) takes 128K tokens, MiniMax M2.5 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-4o (2024-08-06)BarsMiniMax M2.5Ties
Coding03
Intelligence01
Agentic work01
Reasoning05
Math03
Knowledge27
General117
All shared boards337
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench VerifiedNot measured75.8%Only MiniMax M2.5 measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench MultilingualNot measured68.3%Only MiniMax M2.5 measured
LMArena WebDevNot measured1386Only MiniMax M2.5 measured
LiveCodeBench (Vals AI)Not measured79.2%Only MiniMax M2.5 measured
SWE-bench Verified (Vals AI)Not measured74.2%Only MiniMax M2.5 measured
Vibe Code Bench (Vals AI)Not measured14.8%Only MiniMax M2.5 measured
LiveCodeBench (Artificial Analysis run)31.7%Not measuredOnly GPT-4o (2024-08-06) measured
Terminal-Bench Hard (Artificial Analysis run)8.3%34.8%MiniMax M2.5
Terminal-BenchNot measured42.7%Only MiniMax M2.5 measured
ALE-BenchNot measured618.2Only MiniMax M2.5 measured
LMArena Text: coding12831380MiniMax M2.5
LMArena Text: software and IT12781383MiniMax M2.5
LMArena WebDev: ReactNot measured1374Only MiniMax M2.5 measured
LMArena WebDev: HTMLNot measured1414Only MiniMax M2.5 measured
SWE Atlas: Codebase QnANot measured10.3%Only MiniMax M2.5 measured
SWE Atlas: RefactoringNot measured19.5%Only MiniMax M2.5 measured
SWE Atlas: Test WritingNot measured18.6%Only MiniMax M2.5 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
AA Intelligence Index7.722.8MiniMax M2.5
Epoch Capabilities IndexNot measured146.6Only MiniMax M2.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
τ²-Bench Telecom28.9%95.3%MiniMax M2.5
Vending-Bench 2Not measured-$23Only MiniMax M2.5 measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
GPQA DiamondNot measured82.1%Only MiniMax M2.5 measured
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%84.8%MiniMax M2.5
Humanity's Last Exam (Artificial Analysis run)2.3%20.5%MiniMax M2.5
GPQA Diamond (Epoch AI run)49.2%Not measuredOnly GPT-4o (2024-08-06) measured
ARC-AGINot measured63.7%Only MiniMax M2.5 measured
ARC-AGI-2Not measured4.9%Only MiniMax M2.5 measured
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts12641372MiniMax M2.5
LMArena Text: expert12411379MiniMax M2.5
LMArena Text: hard prompts in English12771384MiniMax M2.5
Kagi LLM BenchmarkNot measured55.2%Only MiniMax M2.5 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
AIME14.0%88.8%MiniMax M2.5
MATH 500 (Vals AI)75.2%Not measuredOnly GPT-4o (2024-08-06) measured
MGSM (Vals AI)90.7%Not measuredOnly GPT-4o (2024-08-06) measured
OTIS Mock AIME6.4%Not measuredOnly GPT-4o (2024-08-06) measured
FrontierMath, tiers 1 to 30.4%Not measuredOnly GPT-4o (2024-08-06) measured
ProofBenchNot measured4.0%Only MiniMax M2.5 measured
MATH level 553.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: math12851378MiniMax M2.5
LMArena Text: mathematical work12831378MiniMax M2.5
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index27
Knowledge benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
MMLU Pro74.1%80.1%MiniMax M2.5
LegalBench (Vals AI)80.1%80.0%GPT-4o (2024-08-06)
CaseLaw (Vals AI)Not measured53.5%Only MiniMax M2.5 measured
CorpFin (Vals AI)39.4%59.6%MiniMax M2.5
TaxEval (Vals AI)71.1%68.2%GPT-4o (2024-08-06)
MortgageTax (Vals AI)61.0%Not measuredOnly GPT-4o (2024-08-06) measured
MedQA (Vals AI)88.2%92.5%MiniMax M2.5
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science12741369MiniMax M2.5
LMArena Text: medicine and healthcare12521357MiniMax M2.5
LMArena Text: legal and government12751366MiniMax M2.5
LMArena Text: business and finance12321356MiniMax M2.5
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
Design Arena: websitesNot measured1222Only MiniMax M2.5 measured
Design Arena: UI componentsNot measured1170Only MiniMax M2.5 measured
Design Arena: game devNot measured1176Only MiniMax M2.5 measured
Design Arena: data vizNot measured1172Only MiniMax M2.5 measured
Design Arena: 3DNot measured1170Only MiniMax M2.5 measured
Design Arena: all code categoriesNot measured1207Only MiniMax M2.5 measured
Design Arena: SVGNot measured1150Only MiniMax M2.5 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
General benchmarks for GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
IFBench36.0%71.6%MiniMax M2.5
Long context reasoning (AA-LCR)41.0%73.3%MiniMax M2.5
CL-benchNot measured11.4%Only MiniMax M2.5 measured
CL-bench LifeNot measured6.3%Only MiniMax M2.5 measured
LMArena Text12831359MiniMax M2.5
LMArena Text: instruction following12671353MiniMax M2.5
LMArena Text: creative writing12741331MiniMax M2.5
LMArena Vision1065Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: English12971380MiniMax M2.5
LMArena Text: non-English12621338MiniMax M2.5
LMArena Text: Chinese12541393MiniMax M2.5
LMArena Text: German12571361MiniMax M2.5
LMArena Text: Japanese12341171GPT-4o (2024-08-06)
LMArena Text: Korean12181233MiniMax M2.5
LMArena Text: French12631363MiniMax M2.5
LMArena Text: Spanish12691353MiniMax M2.5
LMArena Text: Russian12721359MiniMax M2.5
LMArena Text: PolishNot measured1334Only MiniMax M2.5 measured
LMArena Text: multi-turn12791364MiniMax M2.5
LMArena Text: longer queries12831366MiniMax M2.5
LMArena Text: writing and language12901345MiniMax M2.5
LMArena Text: entertainment and media12671329MiniMax M2.5
LMArena Vision: English1072Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision: Chinese1009Not measuredOnly GPT-4o (2024-08-06) measured
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 GPT-4o (2024-08-06) and MiniMax M2.5
BenchmarkGPT-4o (2024-08-06)MiniMax M2.5Leader
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-4o (2024-08-06)$0.0075Fits in one request
MiniMax M2.5$0.0009Fits in one request

MiniMax M2.5 costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
MiniMax M2.5$0.019Fits in one request

MiniMax M2.5 costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
MiniMax M2.5$0.072Exceeds the context window

MiniMax M2.5 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-4o (2024-08-06) and MiniMax M2.5
SpecificationOpenAI GPT-4o (2024-08-06)MiniMax M2.5
MakerOpenAIMiniMax
WeightsNo public weights listedOpen weights
ReleasedAugust 6, 2024February 12, 2026
Context window128K205K
Input $/Mtok$2.50$0.30
Output $/Mtok$10.00$1.20
Coding indexNot benchmarked37.2
Independent measurements behind it03
Cost per solved taskNot computable$0.62
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than MiniMax M2.5 for coding?

Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding. Pick GPT-4o (2024-08-06) for work measured by LegalBench (Vals AI) or TaxEval (Vals AI), where it leads.

Which is cheaper, GPT-4o (2024-08-06) or MiniMax M2.5?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; MiniMax M2.5 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.5 only.

Which has the bigger context window, GPT-4o (2024-08-06) or MiniMax M2.5?

MiniMax M2.5, with 205K tokens against 128K.

How many benchmarks is the GPT-4o (2024-08-06) vs MiniMax M2.5 comparison based on?

40 benchmarks have a result for both models as of October 23, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and MiniMax M2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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