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Nova Premier 1.0 vs Qwen3.6 35B A3B

Qwen3.6 35B A3B leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 18.2 to 9.2, and Qwen3.6 35B A3B costs 12.5x less per output token ($1.00 vs $12.50 per million). Updated October 22, 2026; 7 benchmarks have a result for both.

Nova Premier 1.0Amazon
Coding
No data
Overall
No data
Output $/M
$12.50
0
Qwen3.6 35B A3BQwen
Coding
No data
Overall
45.0
Output $/M
$1.00
7
vs boards won of 7 shared

Nova Premier 1.0 or Qwen3.6 35B A3B: which to pick

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

Pick Nova Premier 1.0 for a larger context window (1M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Shared results
7
Nova Premier 1.0 only
7
Qwen3.6 35B A3B only
13
Like-for-like categories
5 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
Nova Premier 1.0 not benchmarked, Qwen3.6 35B A3B not benchmarked.
Widest category
Agentic work, 57.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Nova Premier 1.0 38.3% against Qwen3.6 35B A3B 95.3%, 57.0 points apart on a 0 to 100 scale.
Output price
Nova Premier 1.0 $12.50 against Qwen3.6 35B A3B $1.00 per million output tokens, 12.5x apart.
Context window
Nova Premier 1.0 takes 1M tokens, Qwen3.6 35B A3B 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
CategoryNova Premier 1.0BarsQwen3.6 35B A3BTies
Coding01
Intelligence01
Agentic work01
Reasoning02
General02
All shared boards07
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
AA Coding IndexNot measured41.9Only Qwen3.6 35B A3B measured
LiveCodeBench (Artificial Analysis run)31.7%Not measuredOnly Nova Premier 1.0 measured
SciCodeNot measured36.6%Only Qwen3.6 35B A3B measured
Terminal-Bench Hard (Artificial Analysis run)6.8%34.8%Qwen3.6 35B A3B
Terminal-BenchNot measured24.6%Only Qwen3.6 35B A3B measured
WeirdMLNot measured34.5%Only Qwen3.6 35B A3B measured
ALE-Bench147.4Not measuredOnly Nova Premier 1.0 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 Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
AA Intelligence Index9.218.2Qwen3.6 35B A3B
Epoch Capabilities IndexNot measured143.7Only Qwen3.6 35B A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
AA Agentic IndexNot measured13.1Only Qwen3.6 35B A3B measured
τ²-Bench Telecom38.3%95.3%Qwen3.6 35B A3B
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
GPQA Diamond (Artificial Analysis run)56.9%84.1%Qwen3.6 35B A3B
Humanity's Last Exam (Artificial Analysis run)4.2%22.2%Qwen3.6 35B A3B
GPQA Diamond (Epoch AI run)Not measured84.8%Only Qwen3.6 35B A3B measured
Mystery game puzzlesNot measured22.0%Only Qwen3.6 35B A3B measured
Kagi LLM Benchmark44.8%Not measuredOnly Nova Premier 1.0 measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
AA Math Index17.3Not measuredOnly Nova Premier 1.0 measured
AIME 2025 (Artificial Analysis run)17.3%Not measuredOnly Nova Premier 1.0 measured
OTIS Mock AIMENot measured86.7%Only Qwen3.6 35B A3B measured
FrontierMath, tiers 1 to 3Not measured20.4%Only Qwen3.6 35B A3B measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Knowledge benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
MMLU Pro (Artificial Analysis run)73.3%Not measuredOnly Nova Premier 1.0 measured
Neither model has a result on the other 17 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
Design Arena: websites835Not measuredOnly Nova Premier 1.0 measured
Neither model has a result on the other 8 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
IFBench36.2%64.4%Qwen3.6 35B A3B
Long context reasoning (AA-LCR)34.3%71.7%Qwen3.6 35B A3B
DTBenchNot measured73.9%Only Qwen3.6 35B A3B measured
LMCANot measured29.7%Only Qwen3.6 35B A3B measured
Surface Evolver BenchNot measured44.4%Only Qwen3.6 35B A3B measured
Neither model has a result on the other 41 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Nova Premier 1.0 and Qwen3.6 35B A3B
BenchmarkNova Premier 1.0Qwen3.6 35B A3BLeader
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

Nova Premier 1.0$0.0088Fits in one request
Qwen3.6 35B A3B$0.0006Fits in one request

Qwen3.6 35B A3B costs less

Repository review

50K input + 3K output tokens

Nova Premier 1.0$0.163Fits in one request
Qwen3.6 35B A3B$0.0080Fits in one request

Qwen3.6 35B A3B costs less

Agent loop

200K input + 10K output tokens

Nova Premier 1.0$0.625Fits in one request
Qwen3.6 35B A3B$0.030Fits in one request

Qwen3.6 35B A3B 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 Nova Premier 1.0 and Qwen3.6 35B A3B
SpecificationAmazon Nova Premier 1.0Qwen3.6 35B A3B
MakerAmazonQwen
WeightsNo public weights listedOpen weights
ReleasedOctober 31, 2025April 27, 2026
Context window1M262K
Input $/Mtok$2.50$0.10
Output $/Mtok$12.50$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nova Premier 1.0 better than Qwen3.6 35B A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, Nova Premier 1.0 or Qwen3.6 35B A3B?

Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Nova Premier 1.0 or Qwen3.6 35B A3B?

Nova Premier 1.0, with 1M tokens against 262K.

How many benchmarks is the Nova Premier 1.0 vs Qwen3.6 35B A3B comparison based on?

7 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and Qwen3.6 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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