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Gemma 3 4B vs Qwen3 30B A3B Instruct 2507

Qwen3 30B A3B Instruct 2507 leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 7.5 to 4.8, and Gemma 3 4B costs 4.0x less per output token ($0.075 vs $0.30 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

Gemma 3 4BGoogle
Coding
No data
Overall
22.6
Output $/M
$0.075
0
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
38
vs boards won of 38 shared

Gemma 3 4B 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 Gemma 3 4B for output tokens 4.0x cheaper ($0.075 vs $0.30 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Shared results
38
Gemma 3 4B only
4
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
Gemma 3 4B not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
Widest category
Math, 42.8 points apart on average over 5 shared benchmarks.
Widest single gap
LiveCodeBench (Artificial Analysis run): Gemma 3 4B 11.2% against Qwen3 30B A3B Instruct 2507 70.7%, 59.5 points apart on a 0 to 100 scale.
Output price
Gemma 3 4B $0.075 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 4.0x apart.
Context window
Gemma 3 4B takes 131K 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
CategoryGemma 3 4BBarsQwen3 30B A3B Instruct 2507Ties
Coding04
Intelligence01
Agentic work02
Reasoning06
Math05
Knowledge05
General015
All shared boards038
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
AA Coding Index2.7Not measuredOnly Gemma 3 4B measured
LiveCodeBench (Artificial Analysis run)11.2%70.7%Qwen3 30B A3B Instruct 2507
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)0.8%6.1%Qwen3 30B A3B Instruct 2507
LMArena Text: coding12301416Qwen3 30B A3B Instruct 2507
LMArena Text: software and IT12691417Qwen3 30B A3B Instruct 2507
SciCode0.0%Not measuredOnly Gemma 3 4B 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 Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
AA Intelligence Index4.87.5Qwen3 30B A3B Instruct 2507
Epoch Capabilities Index115.9Not measuredOnly Gemma 3 4B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
τ²-Bench Telecom5.0%28.1%Qwen3 30B A3B Instruct 2507
Berkeley Function Calling Leaderboard (BFCL)19.6%41.4%Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)29.1%70.7%Qwen3 30B A3B Instruct 2507
Humanity's Last Exam (Artificial Analysis run)5.3%10.3%Qwen3 30B A3B Instruct 2507
GPQA Diamond (Epoch AI run)23.2%55.6%Qwen3 30B A3B Instruct 2507
LMArena Text: hard prompts12531398Qwen3 30B A3B Instruct 2507
LMArena Text: expert12231397Qwen3 30B A3B Instruct 2507
LMArena Text: hard prompts in English12531406Qwen3 30B A3B Instruct 2507
Kagi LLM Benchmark25.2%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
AA Math Index12.766.3Qwen3 30B A3B Instruct 2507
AIME 2025 (Artificial Analysis run)12.7%66.3%Qwen3 30B A3B Instruct 2507
OTIS Mock AIME7.5%62.2%Qwen3 30B A3B Instruct 2507
LMArena Text: math12391394Qwen3 30B A3B Instruct 2507
LMArena Text: mathematical work12561411Qwen3 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 Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)41.7%80.5%Qwen3 30B A3B Instruct 2507
LMArena Text: science13061393Qwen3 30B A3B Instruct 2507
LMArena Text: medicine and healthcare13421392Qwen3 30B A3B Instruct 2507
LMArena Text: legal and government13271387Qwen3 30B A3B Instruct 2507
LMArena Text: business and finance13111389Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 13 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 30B A3B Instruct 2507Leader
IFBench28.3%50.7%Qwen3 30B A3B Instruct 2507
Long context reasoning (AA-LCR)6.7%61.3%Qwen3 30B A3B Instruct 2507
DTBench50.9%67.2%Qwen3 30B A3B Instruct 2507
LMCA2.8%22.4%Qwen3 30B A3B Instruct 2507
LMArena Text12911384Qwen3 30B A3B Instruct 2507
LMArena Text: instruction following12391363Qwen3 30B A3B Instruct 2507
LMArena Text: creative writing12701317Qwen3 30B A3B Instruct 2507
LMArena Text: English13001391Qwen3 30B A3B Instruct 2507
LMArena Text: non-English12731372Qwen3 30B A3B Instruct 2507
LMArena Text: ChineseNot measured1432Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: German12811379Qwen3 30B A3B Instruct 2507
LMArena Text: JapaneseNot measured1337Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: KoreanNot measured1330Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: FrenchNot measured1419Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: SpanishNot measured1404Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: Russian12941369Qwen3 30B A3B Instruct 2507
LMArena Text: PolishNot measured1353Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: multi-turn12551378Qwen3 30B A3B Instruct 2507
LMArena Text: longer queries12731378Qwen3 30B A3B Instruct 2507
LMArena Text: writing and language12881336Qwen3 30B A3B Instruct 2507
LMArena Text: entertainment and media12331334Qwen3 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 Gemma 3 4B and Qwen3 30B A3B Instruct 2507
BenchmarkGemma 3 4BQwen3 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

Gemma 3 4B$0.0001Fits in one request
Qwen3 30B A3B Instruct 2507$0.0002Fits in one request

Gemma 3 4B costs less

Repository review

50K input + 3K output tokens

Gemma 3 4B$0.0025Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Gemma 3 4B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 4B$0.0097Exceeds the context window
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Gemma 3 4B 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 Gemma 3 4B and Qwen3 30B A3B Instruct 2507
SpecificationGoogle Gemma 3 4BQwen3 30B A3B Instruct 2507
MakerGoogleQwen
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025July 29, 2025
Context window131K262K
Input $/Mtok$0.045$0.09
Output $/Mtok$0.075$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 4B 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 Gemma 3 4B for output tokens 4.0x cheaper ($0.075 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, Gemma 3 4B or Qwen3 30B A3B Instruct 2507?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 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, Gemma 3 4B or Qwen3 30B A3B Instruct 2507?

Qwen3 30B A3B Instruct 2507, with 262K tokens against 131K.

How many benchmarks is the Gemma 3 4B vs Qwen3 30B A3B Instruct 2507 comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. Gemma 3 4B'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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