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Nemotron 3.5 Super VL vs Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B leads Nemotron 3.5 Super VL on the Artificial Analysis Intelligence Index, 39.9 to 26.5, and Nemotron 3.5 Super VL costs 12.0x less per output token ($0.50 vs $6.00 per million). Updated October 23, 2026; 4 benchmarks have a result for both.

Nemotron 3.5 Super VLNVIDIA
Coding
No data
Overall
35.6
Output $/M
$0.50
0
Qwen3.8 2.4T A95BQwen
Coding
No data
Overall
No data
Output $/M
$6.00
4
vs boards won of 4 shared

Nemotron 3.5 Super VL or Qwen3.8 2.4T A95B: 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 output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and work measured by SciCode or AA Intelligence Index, where it leads.

Shared results
4
Nemotron 3.5 Super VL only
12
Qwen3.8 2.4T A95B only
5
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, Qwen3.8 2.4T A95B not benchmarked.
Widest category
Intelligence, 13.4 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: Nemotron 3.5 Super VL 26.5 against Qwen3.8 2.4T A95B 39.9, 13.4 points apart on a 0 to 100 scale.
Output price
Nemotron 3.5 Super VL $0.50 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 12.0x apart.
Context window
Both take 1.05M tokens.

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 VLBarsQwen3.8 2.4T A95BTies
Coding01
Intelligence01
Reasoning01
General01
All shared boards04
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
LiveBench coding65.5%Not measuredOnly Nemotron 3.5 Super VL measured
AA Coding IndexNot measured71.9Only Qwen3.8 2.4T A95B measured
SciCode47.8%54.1%Qwen3.8 2.4T A95B
Neither model has a result on the other 40 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
AA Intelligence Index26.539.9Qwen3.8 2.4T A95B
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Agentic work benchmarks for Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
AA Agentic IndexNot measured50.1Only Qwen3.8 2.4T A95B measured
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
MCP AtlasNot measured84.5%Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
LiveBench reasoning78.8%Not measuredOnly Nemotron 3.5 Super VL measured
GPQA Diamond (Artificial Analysis run)Not measured93.5%Only Qwen3.8 2.4T A95B measured
Humanity's Last Exam (Artificial Analysis run)30.7%42.4%Qwen3.8 2.4T A95B
Neither model has a result on the other 20 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Math benchmarks for Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
MathArenaNot measured31.6%Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 13 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 Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
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 Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
Design Arena: websites1172Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: UI components1148Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: game dev1110Not measuredOnly Nemotron 3.5 Super VL measured
Design Arena: 3D1127Not 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 Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
LiveBench data analysis64.6%Not measuredOnly Nemotron 3.5 Super VL measured
Long context reasoning (AA-LCR)69.0%80.3%Qwen3.8 2.4T A95B
Neither model has a result on the other 46 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 Qwen3.8 2.4T A95B
BenchmarkNemotron 3.5 Super VLQwen3.8 2.4T A95BLeader
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
Qwen3.8 2.4T A95B$0.0050Fits in one request

Nemotron 3.5 Super VL costs less

Repository review

50K input + 3K output tokens

Nemotron 3.5 Super VL$0.0090Fits in one request
Qwen3.8 2.4T A95B$0.118Fits in one request

Nemotron 3.5 Super VL costs less

Agent loop

200K input + 10K output tokens

Nemotron 3.5 Super VL$0.035Fits in one request
Qwen3.8 2.4T A95B$0.460Fits 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 Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B
SpecificationNVIDIA Nemotron 3.5 Super VLQwen3.8 2.4T A95B
MakerNVIDIAQwen
WeightsOpen weightsOpen weights
ReleasedOctober 15, 2026August 12, 2026
Context window1.05M1.05M
Input $/Mtok$0.15$2.00
Output $/Mtok$0.50$6.00
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 Qwen3.8 2.4T A95B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nemotron 3.5 Super VL for output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and work measured by SciCode or AA Intelligence Index, where it leads.

Which is cheaper, Nemotron 3.5 Super VL or Qwen3.8 2.4T A95B?

Nemotron 3.5 Super VL costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Nemotron 3.5 Super VL or Qwen3.8 2.4T A95B?

Neither: both take 1.05M tokens.

How many benchmarks is the Nemotron 3.5 Super VL vs Qwen3.8 2.4T A95B comparison based on?

4 benchmarks have a result for both models as of October 23, 2026. Nemotron 3.5 Super VL's coding index rests on 1 independent benchmark and Qwen3.8 2.4T A95B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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