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MiniMax M2.7 vs Nemotron 3.5 Super VL

Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

MiniMax M2.7MiniMax
Coding
28.4
Overall
22.8
Output $/M
$1.20
7
Nemotron 3.5 Super VLNVIDIA
Coding
65.5
Overall
26.5
Output $/M
$0.50
2
vs boards won of 9 shared

Decision reading

Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 28.4 for MiniMax M2.7.

Pick MiniMax M2.7 when what matters is SciCode or Design Arena: websites, where it leads.

Shared results
9
MiniMax M2.7 only
65
Nemotron 3.5 Super VL only
7
Like-for-like categories
5 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
MiniMax M2.7 28.4 from 1 benchmark, Nemotron 3.5 Super VL 65.5 from 1 benchmark.
Widest category
Web design, 9.4 points apart on average over 5 shared benchmarks.
Widest single gap
Design Arena: game dev: MiniMax M2.7 1210 against Nemotron 3.5 Super VL 1108, 12.7 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Nemotron 3.5 Super VL $0.50 per million output tokens, 2.4x apart.
Context window
MiniMax M2.7 takes 205K tokens, Nemotron 3.5 Super VL 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
CategoryMiniMax M2.7BarsNemotron 3.5 Super VLTies
Coding10
Intelligence01
Reasoning01
Web design50
General10
All shared boards72
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
Coding benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
LiveBench codingNot measured65.5%Only Nemotron 3.5 Super VL measured
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.6Not measuredOnly MiniMax M2.7 measured
LiveCodeBench (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
SWE-bench Verified (Vals AI)73.8%Not measuredOnly MiniMax M2.7 measured
Vibe Code Bench (Vals AI)11.9%Not measuredOnly MiniMax M2.7 measured
Code migration (Vals AI)8.7%Not measuredOnly MiniMax M2.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)48.7%Not measuredOnly MiniMax M2.7 measured
SciCode50.1%47.8%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)39.4%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3Not measuredOnly MiniMax M2.7 measured
LMArena Text: coding1454Not measuredOnly MiniMax M2.7 measured
LMArena Text: software and IT1446Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: React1388Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: HTML1401Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
AA Intelligence Index22.826.5Nemotron 3.5 Super VL
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
AA Agentic Index15.3Not measuredOnly MiniMax M2.7 measured
LiveBench researchNot measured70.9%Only Nemotron 3.5 Super VL measured
LiveBench browserNot measured4.0%Only Nemotron 3.5 Super VL measured
LiveBench long agenticNot measured15.8%Only Nemotron 3.5 Super VL measured
Finance Agent (Vals AI)27.9%Not measuredOnly MiniMax M2.7 measured
Tax Agent Bench (Vals AI)6.9%Not measuredOnly MiniMax M2.7 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)28.4%Not measuredOnly MiniMax M2.7 measured
τ²-Bench Telecom84.8%Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
LiveBench reasoningNot measured78.8%Only Nemotron 3.5 Super VL measured
GPQA Diamond (Artificial Analysis run)87.4%Not measuredOnly MiniMax M2.7 measured
Humanity's Last Exam (Artificial Analysis run)29.6%30.7%Nemotron 3.5 Super VL
LMArena Text: hard prompts1422Not measuredOnly MiniMax M2.7 measured
LMArena Text: expert1443Not measuredOnly MiniMax M2.7 measured
LMArena Text: hard prompts in English1441Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math1421Not measuredOnly MiniMax M2.7 measured
LMArena Text: mathematical work1437Not measuredOnly MiniMax M2.7 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 MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
MMLU Pro80.4%Not measuredOnly MiniMax M2.7 measured
LegalBench (Vals AI)84.0%Not measuredOnly MiniMax M2.7 measured
CaseLaw (Vals AI)60.9%Not measuredOnly MiniMax M2.7 measured
CorpFin (Vals AI)61.2%Not measuredOnly MiniMax M2.7 measured
TaxEval (Vals AI)66.6%Not measuredOnly MiniMax M2.7 measured
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
LMArena Text: science1416Not measuredOnly MiniMax M2.7 measured
LMArena Text: medicine and healthcare1409Not measuredOnly MiniMax M2.7 measured
LMArena Text: legal and government1403Not measuredOnly MiniMax M2.7 measured
LMArena Text: business and finance1407Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index50
Web design benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
Design Arena: websites12431171MiniMax M2.7
Design Arena: UI components12101148MiniMax M2.7
Design Arena: game dev12101108MiniMax M2.7
Design Arena: data viz1233Not measuredOnly MiniMax M2.7 measured
Design Arena: 3D11951132MiniMax M2.7
Design Arena: all code categories12331155MiniMax M2.7
Design Arena: SVG1136Not measuredOnly MiniMax M2.7 measured
Design Arena: ASCII art1136Not measuredOnly MiniMax M2.7 measured
LiveBench designNot measured60.7%Only Nemotron 3.5 Super VL measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
LiveBench data analysisNot measured64.6%Only Nemotron 3.5 Super VL measured
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
IFBench75.7%Not measuredOnly MiniMax M2.7 measured
Long context reasoning (AA-LCR)78.3%69.0%MiniMax M2.7
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text1405Not measuredOnly MiniMax M2.7 measured
LMArena Text: instruction following1405Not measuredOnly MiniMax M2.7 measured
LMArena Text: creative writing1354Not measuredOnly MiniMax M2.7 measured
LMArena Text: English1426Not measuredOnly MiniMax M2.7 measured
LMArena Text: non-English1382Not measuredOnly MiniMax M2.7 measured
LMArena Text: Chinese1442Not measuredOnly MiniMax M2.7 measured
LMArena Text: German1398Not measuredOnly MiniMax M2.7 measured
LMArena Text: Japanese1260Not measuredOnly MiniMax M2.7 measured
LMArena Text: Korean1314Not measuredOnly MiniMax M2.7 measured
LMArena Text: French1424Not measuredOnly MiniMax M2.7 measured
LMArena Text: Spanish1402Not measuredOnly MiniMax M2.7 measured
LMArena Text: Russian1383Not measuredOnly MiniMax M2.7 measured
LMArena Text: Polish1387Not measuredOnly MiniMax M2.7 measured
LMArena Text: multi-turn1412Not measuredOnly MiniMax M2.7 measured
LMArena Text: longer queries1418Not measuredOnly MiniMax M2.7 measured
LMArena Text: writing and language1376Not measuredOnly MiniMax M2.7 measured
LMArena Text: entertainment and media1360Not measuredOnly MiniMax M2.7 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 MiniMax M2.7 and Nemotron 3.5 Super VL
BenchmarkMiniMax M2.7Nemotron 3.5 Super VLLeader
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

MiniMax M2.7$0.0009Fits in one request
Nemotron 3.5 Super VL$0.0004Fits in one request

Nemotron 3.5 Super VL costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Nemotron 3.5 Super VL$0.0090Fits in one request

Nemotron 3.5 Super VL costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Nemotron 3.5 Super VL$0.035Fits in one request

Nemotron 3.5 Super VL 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 MiniMax M2.7 and Nemotron 3.5 Super VL
SpecificationMiniMax M2.7NVIDIA Nemotron 3.5 Super VL
MakerMiniMaxNVIDIA
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026October 15, 2026
Context window205K1.05M
Input $/Mtok$0.30$0.15
Output $/Mtok$1.20$0.50
Coding index28.465.5
Independent measurements behind it11
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Nemotron 3.5 Super VL for coding?

Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 28.4 for MiniMax M2.7. Pick MiniMax M2.7 when what matters is SciCode or Design Arena: websites, where it leads.

Which is cheaper, MiniMax M2.7 or Nemotron 3.5 Super VL?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Nemotron 3.5 Super VL?

Nemotron 3.5 Super VL, with 1.05M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Nemotron 3.5 Super VL comparison based on?

9 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.7's coding index rests on 1 independent benchmark and Nemotron 3.5 Super VL's on 1. Where only one model has a result, the page says so instead of naming a winner.

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