Enter opens the highlighted result. Esc closes.

GPT-6 Sol vs MiniMax M2.7

GPT-6 Sol leads MiniMax M2.7 on coding, 76.0 to 36.2 on the Vibe Coding Index, and MiniMax M2.7 costs 8.3x less per output token ($1.20 vs $10.00 per million). Updated October 22, 2026; 56 benchmarks have a result for both.

Replace GPT-6 Sol Replace MiniMax M2.7
GPT-6 SolOpenAI
Coding
76.0
Overall
74.6
Output $/M
$10.00
37
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
19
vs boards won of 56 shared

GPT-6 Sol or MiniMax M2.7: which to pick

Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7.

Pick MiniMax M2.7 for output tokens 8.3x cheaper ($1.20 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGPT-6 SolOpenAI76.0/1005 independent benchmarksNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
56
GPT-6 Sol only
45
MiniMax M2.7 only
18
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-6 Sol 76.0 from 5 benchmarks, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Coding, 31.2 points apart on average over 11 shared benchmarks.
Widest single gap
ProofBench: GPT-6 Sol 83.0% against MiniMax M2.7 3.0%, 80.0 points apart on a 0 to 100 scale.
Output price
GPT-6 Sol $10.00 against MiniMax M2.7 $1.20 per million output tokens, 8.3x apart.
Context window
GPT-6 Sol 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-6 SolBarsMiniMax M2.7Ties
Coding92
Intelligence20
Agentic work40
Reasoning13
Math12
Knowledge14
Web design80
General118
All shared boards3719
CodingLike-for-likeSix of these boards feed the Vibe Coding Index92
Coding benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
LiveBench coding93.1%Not measuredOnly GPT-6 Sol measured
LMArena WebDev16831399GPT-6 Sol
AA Coding IndexNot measured52.6Only MiniMax M2.7 measured
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Terminal-Bench 4 (Vals AI)44.4%Not measuredOnly GPT-6 Sol measured
Vibe Code Bench (Vals AI)87.8%11.9%GPT-6 Sol
Code migration (Vals AI)57.2%8.7%GPT-6 Sol
ProgramBench (Vals AI)2.0%0.0%GPT-6 Sol
IOI (Vals AI)82.6%Not measuredOnly GPT-6 Sol measured
Terminal-Bench 2.1 (Vals AI)83.2%48.7%GPT-6 Sol
CyberBench (Vals AI)78.0%Not measuredOnly GPT-6 Sol measured
SciCode57.6%50.1%GPT-6 Sol
Terminal-Bench Hard (Artificial Analysis run)Not measured39.4%Only MiniMax M2.7 measured
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
FrontierCode49.3%Not measuredOnly GPT-6 Sol measured
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-Bench2462.0599.3GPT-6 Sol
LMArena Text: coding14481454MiniMax M2.7
LMArena Text: software and IT14331446MiniMax M2.7
LMArena WebDev: React16851388GPT-6 Sol
LMArena WebDev: HTML16851401GPT-6 Sol
LMArena WebDev: from an image1660Not measuredOnly GPT-6 Sol measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
AA Intelligence Index47.622.8GPT-6 Sol
Epoch Capabilities Index163.7145.8GPT-6 Sol
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
Agentic work benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Design Arena: agents building web apps1231Not measuredOnly GPT-6 Sol measured
Design Arena: agents building full-stack apps1238Not measuredOnly GPT-6 Sol measured
Design Arena: agents building mobile apps1217Not measuredOnly GPT-6 Sol measured
LiveBench research69.3%Not measuredOnly GPT-6 Sol measured
LiveBench browser92.0%Not measuredOnly GPT-6 Sol measured
LiveBench long agentic66.9%Not measuredOnly GPT-6 Sol measured
SREBench (Vals AI)30.5%Not measuredOnly GPT-6 Sol measured
Finance Agent (Vals AI)49.0%27.9%GPT-6 Sol
Tax Agent Bench (Vals AI)15.0%6.9%GPT-6 Sol
Legal Research Bench (Vals AI)28.9%10.6%GPT-6 Sol
Excel Modeling Benchmark (Vals AI)71.5%28.4%GPT-6 Sol
BioMysteryBench (Vals AI)74.8%Not measuredOnly GPT-6 Sol measured
Terminal-Bench-Science (Vals AI)30.0%Not measuredOnly GPT-6 Sol measured
Vals Science Index45.0%Not measuredOnly GPT-6 Sol measured
τ²-Bench TelecomNot measured84.8%Only MiniMax M2.7 measured
APEX-Agents54.3%Not measuredOnly GPT-6 Sol measured
SpireClimb7.5%Not measuredOnly GPT-6 Sol measured
Vending-Bench 2$14,428Not measuredOnly GPT-6 Sol measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
Reasoning benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
LiveBench reasoning88.7%Not measuredOnly GPT-6 Sol measured
MysteryMechanism (Vals AI)30.2%Not measuredOnly GPT-6 Sol measured
GPQA Diamond (Artificial Analysis run)Not measured87.4%Only MiniMax M2.7 measured
Humanity's Last Exam (Artificial Analysis run)47.9%29.6%GPT-6 Sol
GPQA Diamond (Epoch AI run)94.3%Not measuredOnly GPT-6 Sol measured
ARC-AGI95.5%Not measuredOnly GPT-6 Sol measured
ARC-AGI-289.6%Not measuredOnly GPT-6 Sol measured
Chess puzzles56.0%Not measuredOnly GPT-6 Sol measured
Mystery game puzzles56.0%Not measuredOnly GPT-6 Sol measured
EBR-bench53.3%Not measuredOnly GPT-6 Sol measured
LMArena Text: hard prompts14221422MiniMax M2.7
LMArena Text: expert14371443MiniMax M2.7
LMArena Text: hard prompts in English14201441MiniMax M2.7
LMArena Vision: diagrams1270Not measuredOnly GPT-6 Sol measured
LMArena Vision: homework1286Not measuredOnly GPT-6 Sol measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index12
Math benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
OTIS Mock AIME100.0%Not measuredOnly GPT-6 Sol measured
FrontierMath, tiers 1 to 389.8%Not measuredOnly GPT-6 Sol measured
FrontierMath, tier 490.0%Not measuredOnly GPT-6 Sol measured
ProofBench83.0%3.0%GPT-6 Sol
LMArena Text: math14071421MiniMax M2.7
LMArena Text: mathematical work14241437MiniMax M2.7
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)47.1%34.4%GPT-6 Sol
SimpleQA Verified60.7%Not measuredOnly GPT-6 Sol measured
LMArena Text: science13891416MiniMax M2.7
LMArena Text: medicine and healthcare13661409MiniMax M2.7
LMArena Text: legal and government13961403MiniMax M2.7
LMArena Text: business and finance13801407MiniMax M2.7
FACTS Benchmark Suite72.5%Not measuredOnly GPT-6 Sol measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
Design Arena: websites12921243GPT-6 Sol
Design Arena: UI components12901210GPT-6 Sol
Design Arena: game dev13111209GPT-6 Sol
Design Arena: data viz12691233GPT-6 Sol
Design Arena: 3D13141195GPT-6 Sol
Design Arena: all code categories13001233GPT-6 Sol
Design Arena: SVG13151137GPT-6 Sol
Design Arena: ASCII art12221136GPT-6 Sol
LiveBench design82.2%Not measuredOnly GPT-6 Sol measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax M2.7Leader
LiveBench data analysis81.2%Not measuredOnly GPT-6 Sol measured
Public Benefits Bench (Vals AI)56.6%Not measuredOnly GPT-6 Sol measured
SAGE (Vals AI)44.8%Not measuredOnly GPT-6 Sol measured
MedScribe (Vals AI)82.0%79.9%GPT-6 Sol
IFBenchNot measured75.7%Only MiniMax M2.7 measured
Long context reasoning (AA-LCR)83.7%78.3%GPT-6 Sol
DTBench97.3%Not measuredOnly GPT-6 Sol measured
LMCA59.1%Not measuredOnly GPT-6 Sol measured
Furniture assembly58.3%Not measuredOnly GPT-6 Sol measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text13981405MiniMax M2.7
LMArena Text: instruction following14131405GPT-6 Sol
LMArena Text: creative writing13781354GPT-6 Sol
LMArena Vision1240Not measuredOnly GPT-6 Sol measured
LMArena Text: English13961426MiniMax M2.7
LMArena Text: non-English13881382GPT-6 Sol
LMArena Text: Chinese14121442MiniMax M2.7
LMArena Text: German13791398MiniMax M2.7
LMArena Text: Japanese13771260GPT-6 Sol
LMArena Text: Korean13361314GPT-6 Sol
LMArena Text: French13991424MiniMax M2.7
LMArena Text: Spanish13871402MiniMax M2.7
LMArena Text: Russian14021383GPT-6 Sol
LMArena Text: Polish13721387MiniMax M2.7
LMArena Text: multi-turn14141412GPT-6 Sol
LMArena Text: longer queries14161418MiniMax M2.7
LMArena Text: writing and language13891376GPT-6 Sol
LMArena Text: entertainment and media13731360GPT-6 Sol
LMArena Vision: English1229Not measuredOnly GPT-6 Sol measured
LMArena Vision: reading text1258Not measuredOnly GPT-6 Sol measured
LMArena Vision: creative writing1219Not measuredOnly GPT-6 Sol measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-6 Sol and MiniMax M2.7
BenchmarkGPT-6 SolMiniMax 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-6 Sol$0.0070Fits in one request
MiniMax M2.7$0.0009Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

GPT-6 Sol$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-6 Sol$0.500Fits 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-6 Sol and MiniMax M2.7
SpecificationOpenAI GPT-6 SolMiniMax M2.7
MakerOpenAIMiniMax
WeightsNo public weights listedOpen weights
ReleasedSeptember 22, 2026March 18, 2026
Context window1.05M205K
Input $/Mtok$2.00$0.30
Output $/Mtok$10.00$1.20
Coding index76.036.2
Independent measurements behind it53
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-6 Sol better than MiniMax M2.7 for coding?

Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7. Pick MiniMax M2.7 for output tokens 8.3x cheaper ($1.20 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-6 Sol or MiniMax M2.7?

GPT-6 Sol costs $2.00 per million input tokens and $10.00 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-6 Sol or MiniMax M2.7?

GPT-6 Sol, with 1.05M tokens against 205K.

How many benchmarks is the GPT-6 Sol vs MiniMax M2.7 comparison based on?

56 benchmarks have a result for both models as of October 22, 2026. GPT-6 Sol's coding index rests on 5 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.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/gpt-6-sol-vs-minimax-minimax-m2-7" title="GPT-6 Sol 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-6-sol-vs-minimax-minimax-m2-7">LLMBenchmark.ai, GPT-6 Sol vs MiniMax M2.7</a></p>