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Gemma 2 27B vs Qwen3.5-122B-A10B

Gemma 2 27B costs 3.2x less per output token than Qwen3.5-122B-A10B ($0.65 vs $2.08 per million). Updated October 22, 2026; 30 benchmarks have a result for both.

Replace Gemma 2 27B Replace Qwen3.5-122B-A10B
Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
0
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
30
vs boards won of 30 shared

Gemma 2 27B or Qwen3.5-122B-A10B: which to pick

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

Pick Gemma 2 27B for output tokens 3.2x cheaper ($0.65 vs $2.08 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGemma 2 27BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
30
Gemma 2 27B only
6
Qwen3.5-122B-A10B only
21
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
Gemma 2 27B not benchmarked, Qwen3.5-122B-A10B not benchmarked.
Widest category
Reasoning, 39.3 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: expert: Gemma 2 27B 1171 against Qwen3.5-122B-A10B 1431, 43.3 points apart on a 0 to 100 scale.
Output price
Gemma 2 27B $0.65 against Qwen3.5-122B-A10B $2.08 per million output tokens, 3.2x apart.
Context window
Gemma 2 27B takes 8K tokens, Qwen3.5-122B-A10B 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 2 27BBarsQwen3.5-122B-A10BTies
Coding02
Reasoning03
Math02
Knowledge04
General019
All shared boards030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
LMArena WebDevNot measured1361Only Qwen3.5-122B-A10B measured
AA Coding IndexNot measured43.3Only Qwen3.5-122B-A10B measured
SciCodeNot measured39.7%Only Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.1%Only Qwen3.5-122B-A10B measured
LMArena Text: coding12111436Qwen3.5-122B-A10B
LMArena Text: software and IT12281436Qwen3.5-122B-A10B
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTMLNot measured1351Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 35 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
AA Intelligence IndexNot measured17.7Only Qwen3.5-122B-A10B measured
Epoch Capabilities Index122.1Not measuredOnly Gemma 2 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
τ²-Bench TelecomNot measured93.6%Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
GPQA Diamond (Artificial Analysis run)Not measured85.7%Only Qwen3.5-122B-A10B measured
Humanity's Last Exam (Artificial Analysis run)Not measured25.2%Only Qwen3.5-122B-A10B measured
GPQA Diamond (Epoch AI run)36.5%Not measuredOnly Gemma 2 27B measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts11981421Qwen3.5-122B-A10B
LMArena Text: expert11711431Qwen3.5-122B-A10B
LMArena Text: hard prompts in English12061431Qwen3.5-122B-A10B
LMArena Vision: diagramsNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: homeworkNot measured1261Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
OTIS Mock AIME1.4%Not measuredOnly Gemma 2 27B measured
MATH level 527.9%Not measuredOnly Gemma 2 27B measured
LMArena Text: math12121431Qwen3.5-122B-A10B
LMArena Text: mathematical work12211431Qwen3.5-122B-A10B
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
LegalBench (Vals AI)68.0%Not measuredOnly Gemma 2 27B measured
MMLU75.7%Not measuredOnly Gemma 2 27B measured
LMArena Text: science12281432Qwen3.5-122B-A10B
LMArena Text: medicine and healthcare11981423Qwen3.5-122B-A10B
LMArena Text: legal and government12411422Qwen3.5-122B-A10B
LMArena Text: business and finance12081414Qwen3.5-122B-A10B
Neither model has a result on the other 14 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for Gemma 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
IFBenchNot measured75.7%Only Qwen3.5-122B-A10B measured
Long context reasoning (AA-LCR)Not measured76.3%Only Qwen3.5-122B-A10B measured
DTBench48.0%84.3%Qwen3.5-122B-A10B
LMCA7.1%32.2%Qwen3.5-122B-A10B
LMArena Text12311417Qwen3.5-122B-A10B
LMArena Text: instruction following12061399Qwen3.5-122B-A10B
LMArena Text: creative writing12401368Qwen3.5-122B-A10B
LMArena VisionNot measured1244Only Qwen3.5-122B-A10B measured
LMArena Text: English12421428Qwen3.5-122B-A10B
LMArena Text: non-English12171401Qwen3.5-122B-A10B
LMArena Text: Chinese12211463Qwen3.5-122B-A10B
LMArena Text: German12091425Qwen3.5-122B-A10B
LMArena Text: Japanese11751367Qwen3.5-122B-A10B
LMArena Text: Korean11741353Qwen3.5-122B-A10B
LMArena Text: French12481443Qwen3.5-122B-A10B
LMArena Text: Spanish12281425Qwen3.5-122B-A10B
LMArena Text: Russian12341400Qwen3.5-122B-A10B
LMArena Text: Polish12771398Qwen3.5-122B-A10B
LMArena Text: multi-turn12241416Qwen3.5-122B-A10B
LMArena Text: longer queries12301410Qwen3.5-122B-A10B
LMArena Text: writing and language12491387Qwen3.5-122B-A10B
LMArena Text: entertainment and media12121366Qwen3.5-122B-A10B
LMArena Vision: EnglishNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-122B-A10B measured
LMArena Vision: reading textNot measured1251Only Qwen3.5-122B-A10B measured
LMArena Vision: humorNot measured1243Only Qwen3.5-122B-A10B measured
LMArena Vision: creative writingNot measured1220Only Qwen3.5-122B-A10B 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 2 27B and Qwen3.5-122B-A10B
BenchmarkGemma 2 27BQwen3.5-122B-A10BLeader
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 2 27B$0.0010Fits in one request
Qwen3.5-122B-A10B$0.0013Fits in one request

Gemma 2 27B costs less

Repository review

50K input + 3K output tokens

Gemma 2 27B$0.034Exceeds the context window
Qwen3.5-122B-A10B$0.019Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Gemma 2 27B$0.137Exceeds the context window
Qwen3.5-122B-A10B$0.073Fits in one request

Qwen3.5-122B-A10B 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 2 27B and Qwen3.5-122B-A10B
SpecificationGoogle Gemma 2 27BQwen3.5-122B-A10B
MakerGoogleQwen
WeightsOpen weightsOpen weights
ReleasedJuly 13, 2024February 25, 2026
Context window8K262K
Input $/Mtok$0.65$0.26
Output $/Mtok$0.65$2.08
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 2 27B better than Qwen3.5-122B-A10B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 2 27B for output tokens 3.2x cheaper ($0.65 vs $2.08 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Gemma 2 27B or Qwen3.5-122B-A10B?

Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 2 27B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B, with 262K tokens against 8K.

How many benchmarks is the Gemma 2 27B vs Qwen3.5-122B-A10B comparison based on?

30 benchmarks have a result for both models as of October 22, 2026. Gemma 2 27B's coding index rests on 0 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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