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Devstral 2 2512 vs Nemotron 3.5 Super VL

Updated October 21, 2026. 1 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Devstral 2 2512Mistral AI
Coding
53.8
Overall
8.6
Output $/M
$2.00
0
Nemotron 3.5 Super VLNVIDIA
Coding
65.5
Overall
26.5
Output $/M
$0.50
1
vs boards won of 1 shared

Decision reading

Devstral 2 2512 scores 53.8 and Nemotron 3.5 Super VL 65.5 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking.

Pick Nemotron 3.5 Super VL when output tokens cost 4.0x less, or when the context window is larger, 1.05M against 262K tokens.

Shared results
1
Devstral 2 2512 only
5
Nemotron 3.5 Super VL only
15
Like-for-like categories
1 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
Devstral 2 2512 53.8 from 1 benchmark, Nemotron 3.5 Super VL 65.5 from 1 benchmark.
Widest category
Intelligence, 17.9 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: Devstral 2 2512 8.6 against Nemotron 3.5 Super VL 26.5, 17.9 points apart on a 0 to 100 scale.
Output price
Devstral 2 2512 $2.00 against Nemotron 3.5 Super VL $0.50 per million output tokens, 4.0x apart.
Context window
Devstral 2 2512 takes 262K 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
CategoryDevstral 2 2512BarsNemotron 3.5 Super VLTies
Intelligence01
All shared boards01
CodingDirectional onlyFour of these boards feed the Vibe Coding Index6 boards, none shared
Coding benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
SWE-bench Verified53.8%Not measuredOnly Devstral 2 2512 measured
LiveBench codingNot measured65.5%Only Nemotron 3.5 Super VL measured
AA Coding Index31.3Not measuredOnly Devstral 2 2512 measured
LiveCodeBench (Vals AI)51.8%Not measuredOnly Devstral 2 2512 measured
SWE-bench Verified (Vals AI)62.8%Not measuredOnly Devstral 2 2512 measured
SciCodeNot measured47.8%Only Nemotron 3.5 Super VL measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
AA Intelligence Index8.626.5Nemotron 3.5 Super VL
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
AA Agentic Index2.3Not measuredOnly Devstral 2 2512 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
Neither model has a result on the other 35 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Reasoning benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
LiveBench reasoningNot measured78.8%Only Nemotron 3.5 Super VL measured
Humanity's Last Exam (Artificial Analysis run)Not measured30.7%Only Nemotron 3.5 Super VL measured
Neither model has a result on the other 19 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
Neither model has a result on 13 boards here
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Knowledge benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
Neither model has a result on 17 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
Design Arena: websitesNot measured1171Only Nemotron 3.5 Super VL measured
Design Arena: UI componentsNot measured1148Only Nemotron 3.5 Super VL measured
Design Arena: game devNot measured1108Only Nemotron 3.5 Super VL measured
Design Arena: 3DNot measured1132Only Nemotron 3.5 Super VL measured
Design Arena: all code categoriesNot measured1155Only Nemotron 3.5 Super VL measured
LiveBench designNot measured60.7%Only Nemotron 3.5 Super VL measured
Neither model has a result on the other 3 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
General benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 3.5 Super VLLeader
LiveBench data analysisNot measured64.6%Only Nemotron 3.5 Super VL measured
Long context reasoning (AA-LCR)Not measured69.0%Only Nemotron 3.5 Super VL measured
Neither model has a result on the other 44 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Devstral 2 2512 and Nemotron 3.5 Super VL
BenchmarkDevstral 2 2512Nemotron 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

Devstral 2 2512$0.0014Fits 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

Devstral 2 2512$0.026Fits 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

Devstral 2 2512$0.100Fits in one request
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 Devstral 2 2512 and Nemotron 3.5 Super VL
SpecificationMistral Devstral 2 2512NVIDIA Nemotron 3.5 Super VL
MakerMistral AINVIDIA
WeightsOpen weightsOpen weights
ReleasedDecember 9, 2025October 15, 2026
Context window262K1.05M
Input $/Mtok$0.40$0.15
Output $/Mtok$2.00$0.50
Coding index53.865.5
Independent measurements behind it11
Cost per solved task$1.19Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Devstral 2 2512 better than Nemotron 3.5 Super VL for coding?

Devstral 2 2512 scores 53.8 and Nemotron 3.5 Super VL 65.5 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking. Pick Nemotron 3.5 Super VL when output tokens cost 4.0x less, or when the context window is larger, 1.05M against 262K tokens.

Which is cheaper, Devstral 2 2512 or Nemotron 3.5 Super VL?

Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for Devstral 2 2512 only.

Which has the bigger context window, Devstral 2 2512 or Nemotron 3.5 Super VL?

Nemotron 3.5 Super VL, with 1.05M tokens against 262K.

How many benchmarks is the Devstral 2 2512 vs Nemotron 3.5 Super VL comparison based on?

1 benchmarks have a result for both models as of October 21, 2026. Devstral 2 2512'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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