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Nova Micro 1.0 vs Qwen3 30B A3B Instruct 2507

Qwen3 30B A3B Instruct 2507 leads Nova Micro 1.0 on the Artificial Analysis Intelligence Index, 7.5 to 5.9, and Nova Micro 1.0 costs 2.1x less per output token ($0.14 vs $0.30 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

Replace Nova Micro 1.0 Replace Qwen3 30B A3B Instruct 2507
Nova Micro 1.0Amazon
Coding
No data
Overall
No data
Output $/M
$0.14
0
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
38
vs boards won of 38 shared

Nova Micro 1.0 or Qwen3 30B A3B Instruct 2507: which to pick

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

Pick Nova Micro 1.0 for output tokens 2.1x cheaper ($0.14 vs $0.30 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model ANova Micro 1.0AmazonNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3 30B A3B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
38
Nova Micro 1.0 only
1
Qwen3 30B A3B Instruct 2507 only
7
Like-for-like categories
7 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 Micro 1.0 not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
Widest category
Math, 46.3 points apart on average over 4 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): Nova Micro 1.0 6.0% against Qwen3 30B A3B Instruct 2507 66.3%, 60.3 points apart on a 0 to 100 scale.
Output price
Nova Micro 1.0 $0.14 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 2.1x apart.
Context window
Nova Micro 1.0 takes 128K tokens, Qwen3 30B A3B Instruct 2507 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 Micro 1.0BarsQwen3 30B A3B Instruct 2507Ties
Coding04
Intelligence01
Agentic work01
Reasoning05
Math04
Knowledge05
General018
All shared boards038
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
LiveCodeBench (Artificial Analysis run)14.0%70.7%Qwen3 30B A3B Instruct 2507
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)1.5%6.1%Qwen3 30B A3B Instruct 2507
LMArena Text: coding12181416Qwen3 30B A3B Instruct 2507
LMArena Text: software and IT12151417Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
AA Intelligence Index5.97.5Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
τ²-Bench Telecom14.0%28.1%Qwen3 30B A3B Instruct 2507
Berkeley Function Calling Leaderboard (BFCL)Not measured41.4%Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)35.8%70.7%Qwen3 30B A3B Instruct 2507
Humanity's Last Exam (Artificial Analysis run)4.6%10.3%Qwen3 30B A3B Instruct 2507
GPQA Diamond (Epoch AI run)Not measured55.6%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: hard prompts11911398Qwen3 30B A3B Instruct 2507
LMArena Text: expert11831397Qwen3 30B A3B Instruct 2507
LMArena Text: hard prompts in English12031406Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
AA Math Index6.066.3Qwen3 30B A3B Instruct 2507
AIME 2025 (Artificial Analysis run)6.0%66.3%Qwen3 30B A3B Instruct 2507
OTIS Mock AIMENot measured62.2%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: math12061394Qwen3 30B A3B Instruct 2507
LMArena Text: mathematical work12121411Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)53.1%80.5%Qwen3 30B A3B Instruct 2507
MMLU70.8%Not measuredOnly Nova Micro 1.0 measured
LMArena Text: science12101393Qwen3 30B A3B Instruct 2507
LMArena Text: medicine and healthcare12071392Qwen3 30B A3B Instruct 2507
LMArena Text: legal and government12211387Qwen3 30B A3B Instruct 2507
LMArena Text: business and finance11821389Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 12 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
IFBench29.4%50.7%Qwen3 30B A3B Instruct 2507
Long context reasoning (AA-LCR)13.0%61.3%Qwen3 30B A3B Instruct 2507
DTBenchNot measured67.2%Only Qwen3 30B A3B Instruct 2507 measured
LMCANot measured22.4%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text12081384Qwen3 30B A3B Instruct 2507
LMArena Text: instruction following11741363Qwen3 30B A3B Instruct 2507
LMArena Text: creative writing11721317Qwen3 30B A3B Instruct 2507
LMArena Text: English12241391Qwen3 30B A3B Instruct 2507
LMArena Text: non-English11861372Qwen3 30B A3B Instruct 2507
LMArena Text: Chinese12091432Qwen3 30B A3B Instruct 2507
LMArena Text: German11921379Qwen3 30B A3B Instruct 2507
LMArena Text: Japanese11541337Qwen3 30B A3B Instruct 2507
LMArena Text: Korean11501330Qwen3 30B A3B Instruct 2507
LMArena Text: French12381419Qwen3 30B A3B Instruct 2507
LMArena Text: Spanish12251404Qwen3 30B A3B Instruct 2507
LMArena Text: Russian11851369Qwen3 30B A3B Instruct 2507
LMArena Text: PolishNot measured1353Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: multi-turn11781378Qwen3 30B A3B Instruct 2507
LMArena Text: longer queries12051378Qwen3 30B A3B Instruct 2507
LMArena Text: writing and language11921336Qwen3 30B A3B Instruct 2507
LMArena Text: entertainment and media11631334Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Nova Micro 1.0 and Qwen3 30B A3B Instruct 2507
BenchmarkNova Micro 1.0Qwen3 30B A3B Instruct 2507Leader
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 Micro 1.0$0.0001Fits in one request
Qwen3 30B A3B Instruct 2507$0.0002Fits in one request

Nova Micro 1.0 costs less

Repository review

50K input + 3K output tokens

Nova Micro 1.0$0.0022Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Nova Micro 1.0 costs less

Agent loop

200K input + 10K output tokens

Nova Micro 1.0$0.0084Exceeds the context window
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Nova Micro 1.0 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 Micro 1.0 and Qwen3 30B A3B Instruct 2507
SpecificationAmazon Nova Micro 1.0Qwen3 30B A3B Instruct 2507
MakerAmazonQwen
WeightsNo public weights listedOpen weights
ReleasedDecember 5, 2024July 29, 2025
Context window128K262K
Input $/Mtok$0.035$0.09
Output $/Mtok$0.14$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nova Micro 1.0 better than Qwen3 30B A3B Instruct 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Micro 1.0 for output tokens 2.1x cheaper ($0.14 vs $0.30 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Nova Micro 1.0 or Qwen3 30B A3B Instruct 2507?

Nova Micro 1.0 costs $0.035 per million input tokens and $0.14 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Nova Micro 1.0 or Qwen3 30B A3B Instruct 2507?

Qwen3 30B A3B Instruct 2507, with 262K tokens against 128K.

How many benchmarks is the Nova Micro 1.0 vs Qwen3 30B A3B Instruct 2507 comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. Nova Micro 1.0's coding index rests on 0 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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