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Gemma 4 26B A4B vs Qwen3.5-9B

Gemma 4 26B A4B leads Qwen3.5-9B on the Artificial Analysis Intelligence Index, 16.7 to 13.3, and Qwen3.5-9B costs 4.0x less per output token ($0.15 vs $0.60 per million). Updated October 22, 2026; 14 benchmarks have a result for both.

Gemma 4 26B A4BGoogle
Coding
No data
Overall
54.7
Output $/M
$0.60
10
Qwen3.5-9BQwen
Coding
No data
Overall
No data
Output $/M
$0.15
4
vs boards won of 14 shared

Gemma 4 26B A4B or Qwen3.5-9B: which to pick

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

Pick Gemma 4 26B A4B for work measured by τ²-Bench Telecom or GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
14
Gemma 4 26B A4B only
41
Qwen3.5-9B only
1
Like-for-like categories
6 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 4 26B A4B not benchmarked, Qwen3.5-9B not benchmarked.
Widest category
Agentic work, 43.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against Qwen3.5-9B 86.8%, 43.3 points apart on a 0 to 100 scale.
Output price
Gemma 4 26B A4B $0.60 against Qwen3.5-9B $0.15 per million output tokens, 4.0x apart.
Context window
Both take 262K 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
CategoryGemma 4 26B A4BBarsQwen3.5-9BTies
Coding30
Intelligence20
Agentic work01
Reasoning12
Math10
General31
All shared boards104
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
LMArena WebDev1360Not measuredOnly Gemma 4 26B A4B measured
AA Coding Index39.323.5Gemma 4 26B A4B
SciCode40.0%29.5%Gemma 4 26B A4B
Terminal-Bench Hard (Artificial Analysis run)25.0%24.2%Gemma 4 26B A4B
Terminal-BenchNot measured9.2%Only Qwen3.5-9B measured
WeirdML35.2%Not measuredOnly Gemma 4 26B A4B measured
ALE-Bench927.2Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: coding1446Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: software and IT1454Not measuredOnly Gemma 4 26B A4B measured
LMArena WebDev: React1351Not measuredOnly Gemma 4 26B A4B measured
LMArena WebDev: HTML1362Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
AA Intelligence Index16.713.3Gemma 4 26B A4B
Epoch Capabilities Index141.9139.3Gemma 4 26B A4B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
AA Agentic Index2.9Not measuredOnly Gemma 4 26B A4B measured
τ²-Bench Telecom43.6%86.8%Qwen3.5-9B
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
Reasoning benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
GPQA Diamond (Artificial Analysis run)79.2%80.6%Qwen3.5-9B
Humanity's Last Exam (Artificial Analysis run)19.3%14.9%Gemma 4 26B A4B
GPQA Diamond (Epoch AI run)73.2%79.0%Qwen3.5-9B
LMArena Text: hard prompts1438Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: expert1447Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: hard prompts in English1448Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: diagrams1264Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: homework1293Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
OTIS Mock AIME82.2%61.7%Gemma 4 26B A4B
LMArena Text: math1470Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: mathematical work1475Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
LMArena Text: science1446Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: medicine and healthcare1428Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: legal and government1457Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: business and finance1429Not measuredOnly Gemma 4 26B A4B measured
FACTS Benchmark Suite42.7%Not measuredOnly Gemma 4 26B A4B measured
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 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
General benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
IFBench72.4%66.7%Gemma 4 26B A4B
Long context reasoning (AA-LCR)65.7%70.0%Qwen3.5-9B
DTBench74.9%71.2%Gemma 4 26B A4B
LMCA29.7%24.5%Gemma 4 26B A4B
LMArena Text1434Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: instruction following1420Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: creative writing1400Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision1260Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: English1444Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: non-English1421Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: Chinese1495Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: French1460Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: Spanish1415Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: Russian1434Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: multi-turn1441Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: longer queries1427Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: writing and language1405Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: entertainment and media1403Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: English1256Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: Chinese1312Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: reading text1268Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: humor1272Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: captioning1297Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: recognizing things1191Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: creative writing1256Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 26B A4B and Qwen3.5-9B
BenchmarkGemma 4 26B A4BQwen3.5-9BLeader
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

Gemma 4 26B A4B$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

Gemma 4 26B A4B$0.0093Fits in one request
Qwen3.5-9B$0.0054Fits in one request

Qwen3.5-9B costs less

Agent loop

200K input + 10K output tokens

Gemma 4 26B A4B$0.036Fits 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 Gemma 4 26B A4B and Qwen3.5-9B
SpecificationGoogle Gemma 4 26B A4BQwen3.5-9B
MakerGoogleQwen
WeightsOpen weightsOpen weights
ReleasedApril 3, 2026March 10, 2026
Context window262K262K
Input $/Mtok$0.15$0.10
Output $/Mtok$0.60$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 26B A4B better than Qwen3.5-9B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 4 26B A4B for work measured by τ²-Bench Telecom or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 4 26B A4B or Qwen3.5-9B?

Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 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, Gemma 4 26B A4B or Qwen3.5-9B?

Neither: both take 262K tokens.

How many benchmarks is the Gemma 4 26B A4B vs Qwen3.5-9B comparison based on?

14 benchmarks have a result for both models as of October 22, 2026. Gemma 4 26B A4B'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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