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Gemma 3 27B vs Qwen3.5-27B

Updated October 21, 2026. 47 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemma 3 27B Replace Qwen3.5-27B
Gemma 3 27BGoogle
Coding
4.9
Overall
4.9
Output $/M
$0.35
0
Qwen3.5-27BQwen
Coding
22.6
Overall
22.9
Output $/M
$2.16
47
vs boards won of 47 shared

Decision reading

Pick Qwen3.5-27B for coding: it scores 22.6 on the Vibe Coding Index against 4.9 for Gemma 3 27B.

Pick Gemma 3 27B when output tokens cost 6.2x less.

Model AGemma 3 27BGoogle4.9/1001 independent benchmarkNo cost per solved taskModel BQwen3.5-27BQwen22.6/1001 independent benchmarkNo cost per solved task
Shared results
47
Gemma 3 27B only
15
Qwen3.5-27B only
6
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 27B 4.9 from 1 benchmark, Qwen3.5-27B 22.6 from 1 benchmark.
Widest category
Agentic work, 83.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 3 27B 10.5% against Qwen3.5-27B 93.9%, 83.3 points apart on a 0 to 100 scale.
Output price
Gemma 3 27B $0.35 against Qwen3.5-27B $2.16 per million output tokens, 6.2x apart.
Context window
Gemma 3 27B takes 131K tokens, Qwen3.5-27B 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 27BBarsQwen3.5-27BTies
Coding03
Intelligence01
Agentic work01
Reasoning07
Math02
Knowledge04
General029
All shared boards047
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
Coding benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
Aider polyglot4.9%Not measuredOnly Gemma 3 27B measured
LMArena WebDevNot measured1358Only Qwen3.5-27B measured
AA Coding Index10.1Not measuredOnly Gemma 3 27B measured
LiveCodeBench (Artificial Analysis run)13.7%Not measuredOnly Gemma 3 27B measured
SciCode23.3%Not measuredOnly Gemma 3 27B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%32.6%Qwen3.5-27B
WeirdMLNot measured39.5%Only Qwen3.5-27B measured
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding13221427Qwen3.5-27B
LMArena Text: software and IT13541431Qwen3.5-27B
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTMLNot measured1386Only Qwen3.5-27B measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
AA Intelligence Index4.922.9Qwen3.5-27B
Epoch Capabilities Index130.0Not measuredOnly Gemma 3 27B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
AA Agentic Index0.1Not measuredOnly Gemma 3 27B measured
τ²-Bench Telecom10.5%93.9%Qwen3.5-27B
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
GPQA Diamond (Artificial Analysis run)42.8%85.8%Qwen3.5-27B
Humanity's Last Exam (Artificial Analysis run)4.4%23.9%Qwen3.5-27B
GPQA Diamond (Epoch AI run)47.7%Not measuredOnly Gemma 3 27B measured
LMArena Text: hard prompts13401415Qwen3.5-27B
LMArena Text: expert13041427Qwen3.5-27B
LMArena Text: hard prompts in English13531429Qwen3.5-27B
LMArena Vision: diagrams11561249Qwen3.5-27B
LMArena Vision: homework11601256Qwen3.5-27B
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
AA Math Index20.7Not measuredOnly Gemma 3 27B measured
AIME 2025 (Artificial Analysis run)20.7%Not measuredOnly Gemma 3 27B measured
OTIS Mock AIME22.5%Not measuredOnly Gemma 3 27B measured
MATH level 574.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: math13121429Qwen3.5-27B
LMArena Text: mathematical work13271429Qwen3.5-27B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
MMLU Pro (Artificial Analysis run)66.9%Not measuredOnly Gemma 3 27B measured
GeoBench52.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: science13831437Qwen3.5-27B
LMArena Text: medicine and healthcare13911425Qwen3.5-27B
LMArena Text: legal and government13751405Qwen3.5-27B
LMArena Text: business and finance13601399Qwen3.5-27B
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index029
General benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
IFBench31.8%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)7.3%77.7%Qwen3.5-27B
DTBench52.5%82.4%Qwen3.5-27B
LMCA12.3%34.0%Qwen3.5-27B
Fiction.LiveBench33.3%Not measuredOnly Gemma 3 27B measured
Creative writing (Lech Mazur)79.9%Not measuredOnly Gemma 3 27B measured
LMArena Text13581409Qwen3.5-27B
LMArena Text: instruction following13211393Qwen3.5-27B
LMArena Text: creative writing13451362Qwen3.5-27B
LMArena Vision11651241Qwen3.5-27B
LMArena Text: English13771425Qwen3.5-27B
LMArena Text: non-English13341390Qwen3.5-27B
LMArena Text: Chinese13461478Qwen3.5-27B
LMArena Text: German13621392Qwen3.5-27B
LMArena Text: Japanese12871346Qwen3.5-27B
LMArena Text: Korean13081359Qwen3.5-27B
LMArena Text: French13681410Qwen3.5-27B
LMArena Text: Spanish13491407Qwen3.5-27B
LMArena Text: Russian13491390Qwen3.5-27B
LMArena Text: Polish13451375Qwen3.5-27B
LMArena Text: multi-turn13451410Qwen3.5-27B
LMArena Text: longer queries13331413Qwen3.5-27B
LMArena Text: writing and language13471380Qwen3.5-27B
LMArena Text: entertainment and media13201363Qwen3.5-27B
LMArena Vision: English11881246Qwen3.5-27B
LMArena Vision: Chinese11641301Qwen3.5-27B
LMArena Vision: reading text11561246Qwen3.5-27B
LMArena Vision: humor11661227Qwen3.5-27B
LMArena Vision: captioning11511170Qwen3.5-27B
LMArena Vision: recognizing things11961210Qwen3.5-27B
LMArena Vision: creative writing11771224Qwen3.5-27B
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 3 27B and Qwen3.5-27B
BenchmarkGemma 3 27BQwen3.5-27BLeader
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 27B$0.0003Fits in one request
Qwen3.5-27B$0.0014Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Gemma 3 27B$0.0050Fits in one request
Qwen3.5-27B$0.020Fits in one request

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 27B$0.019Exceeds the context window
Qwen3.5-27B$0.076Fits in one request

Gemma 3 27B 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 27B and Qwen3.5-27B
SpecificationGoogle Gemma 3 27BQwen3.5-27B
MakerGoogleQwen
WeightsOpen weightsOpen weights
ReleasedMarch 12, 2025February 25, 2026
Context window131K262K
Input $/Mtok$0.08$0.27
Output $/Mtok$0.35$2.16
Coding index4.922.6
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 27B better than Qwen3.5-27B for coding?

Pick Qwen3.5-27B for coding: it scores 22.6 on the Vibe Coding Index against 4.9 for Gemma 3 27B. Pick Gemma 3 27B when output tokens cost 6.2x less.

Which is cheaper, Gemma 3 27B or Qwen3.5-27B?

Gemma 3 27B costs $0.08 per million input tokens and $0.35 per million output tokens; Qwen3.5-27B costs $0.27 and $2.16. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 3 27B or Qwen3.5-27B?

Qwen3.5-27B, with 262K tokens against 131K.

How many benchmarks is the Gemma 3 27B vs Qwen3.5-27B comparison based on?

47 benchmarks have a result for both models as of October 21, 2026. Gemma 3 27B's coding index rests on 1 independent benchmark and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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