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Nemotron 3.5 Super VL vs Qwen3.5-9B

Nemotron 3.5 Super VL leads Qwen3.5-9B on the Artificial Analysis Intelligence Index, 26.5 to 13.3, and Qwen3.5-9B costs 3.3x less per output token ($0.15 vs $0.50 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

Nemotron 3.5 Super VLNVIDIA
Coding
No data
Overall
35.6
Output $/M
$0.50
3
Qwen3.5-9BQwen
Coding
No data
Overall
No data
Output $/M
$0.15
1
vs boards won of 4 shared

Nemotron 3.5 Super VL or Qwen3.5-9B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Nemotron 3.5 Super VL for a larger context window (1.05M against 262K tokens) and work measured by Long context reasoning (AA-LCR), where it leads.

Shared results
4
Nemotron 3.5 Super VL only
12
Qwen3.5-9B only
12
Like-for-like categories
4 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
Nemotron 3.5 Super VL not benchmarked, Qwen3.5-9B not benchmarked.
Widest category
Coding, 18.3 points apart on average over 1 shared benchmark.
Widest single gap
SciCode: Nemotron 3.5 Super VL 47.8% against Qwen3.5-9B 29.5%, 18.3 points apart on a 0 to 100 scale.
Output price
Nemotron 3.5 Super VL $0.50 against Qwen3.5-9B $0.15 per million output tokens, 3.3x apart.
Context window
Nemotron 3.5 Super VL takes 1.05M tokens, Qwen3.5-9B 262K.

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
CategoryNemotron 3.5 Super VLBarsQwen3.5-9BTies
Coding10
Intelligence10
Reasoning10
General01
All shared boards31
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
LiveBench coding65.5%Not measuredOnly Nemotron 3.5 Super VL measured
AA Coding IndexNot measured23.5Only Qwen3.5-9B measured
SciCode47.8%29.5%Nemotron 3.5 Super VL
Terminal-Bench Hard (Artificial Analysis run)Not measured24.2%Only Qwen3.5-9B measured
Terminal-BenchNot measured9.2%Only Qwen3.5-9B measured
Neither model has a result on the other 38 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
AA Intelligence Index26.513.3Nemotron 3.5 Super VL
Epoch Capabilities IndexNot measured139.3Only Qwen3.5-9B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
LiveBench research70.9%Not measuredOnly Nemotron 3.5 Super VL measured
LiveBench browser4.0%Not measuredOnly Nemotron 3.5 Super VL measured
LiveBench long agentic15.8%Not measuredOnly Nemotron 3.5 Super VL measured
τ²-Bench TelecomNot measured86.8%Only Qwen3.5-9B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
LiveBench reasoning78.8%Not measuredOnly Nemotron 3.5 Super VL measured
GPQA Diamond (Artificial Analysis run)Not measured80.6%Only Qwen3.5-9B measured
Humanity's Last Exam (Artificial Analysis run)30.7%14.9%Nemotron 3.5 Super VL
GPQA Diamond (Epoch AI run)Not measured79.0%Only Qwen3.5-9B measured
Neither model has a result on the other 19 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
OTIS Mock AIMENot measured61.7%Only Qwen3.5-9B measured
MathArenaNot measured13.0%Only Qwen3.5-9B measured
Neither model has a result on the other 12 boards here
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Knowledge benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
Neither model has a result on 20 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
Design Arena: websites1173Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: UI components1149Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: game dev1110Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: 3D1128Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: all code categories1154Not measuredOnly Nemotron 3.5 Super VL measured
LiveBench design60.7%Not measuredOnly Nemotron 3.5 Super VL measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
General benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
LiveBench data analysis64.6%Not measuredOnly Nemotron 3.5 Super VL measured
IFBenchNot measured66.7%Only Qwen3.5-9B measured
Long context reasoning (AA-LCR)69.0%70.0%Qwen3.5-9B
DTBenchNot measured71.2%Only Qwen3.5-9B measured
LMCANot measured24.5%Only Qwen3.5-9B measured
Neither model has a result on the other 43 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Nemotron 3.5 Super VL and Qwen3.5-9B
BenchmarkNemotron 3.5 Super VLQwen3.5-9BLeader
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

Nemotron 3.5 Super VL$0.0004Fits in one request
Qwen3.5-9B$0.0002Fits in one request

Qwen3.5-9B costs less

Repository review

50K input + 3K output tokens

Nemotron 3.5 Super VL$0.0090Fits in one request
Qwen3.5-9B$0.0054Fits in one request

Qwen3.5-9B costs less

Agent loop

200K input + 10K output tokens

Nemotron 3.5 Super VL$0.035Fits in one request
Qwen3.5-9B$0.021Fits in one request

Qwen3.5-9B 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 Nemotron 3.5 Super VL and Qwen3.5-9B
SpecificationNVIDIA Nemotron 3.5 Super VLQwen3.5-9B
MakerNVIDIAQwen
WeightsOpen weightsOpen weights
ReleasedOctober 15, 2026March 10, 2026
Context window1.05M262K
Input $/Mtok$0.15$0.10
Output $/Mtok$0.50$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nemotron 3.5 Super VL better than Qwen3.5-9B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nemotron 3.5 Super VL for a larger context window (1.05M against 262K tokens) and work measured by Long context reasoning (AA-LCR), where it leads.

Which is cheaper, Nemotron 3.5 Super VL or Qwen3.5-9B?

Nemotron 3.5 Super VL costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.

Which has the bigger context window, Nemotron 3.5 Super VL or Qwen3.5-9B?

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

How many benchmarks is the Nemotron 3.5 Super VL vs Qwen3.5-9B comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. Nemotron 3.5 Super VL's coding index rests on 1 independent benchmark and Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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