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Gemma 3 27B vs Moondream 3 Preview

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemma 3 27BGoogle
Coding
No data
Overall
4.9
Output $/M
$0.30
M Moondream 3 PreviewMoondream
Coding
No data
Overall
No data
Output $/M
$2.50
vs $0.30 vs $2.50 per 1M output tokens. Gemma 3 27B is 8.3x cheaper.

Decision reading

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

Gemma 3 27B has the edge where output tokens cost 8.3x less, and where the context window is larger, 131K against 32K tokens.

Shared results
0
Gemma 3 27B only
62
Moondream 3 Preview only
0
Like-for-like categories
0 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 not benchmarked, Moondream 3 Preview not benchmarked.
Widest category
No category has a result for both models.
Widest single gap
No benchmark has a result for both models.
Output price
Gemma 3 27B $0.30 against Moondream 3 Preview $2.50 per million output tokens, 8.3x apart.
Context window
Gemma 3 27B takes 131K tokens, Moondream 3 Preview 32K.

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.

CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
Coding benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
Aider polyglot4.9%Not measuredOnly Gemma 3 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%Not measuredOnly Gemma 3 27B measured
LMArena Text: coding1322Not measuredOnly Gemma 3 27B measured
LMArena Text: software and IT1354Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
AA Intelligence Index4.9Not measuredOnly Gemma 3 27B measured
Epoch Capabilities Index130.0Not measuredOnly Gemma 3 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
AA Agentic Index0.1Not measuredOnly Gemma 3 27B measured
τ²-Bench Telecom10.5%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 37 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Reasoning benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
GPQA Diamond (Artificial Analysis run)42.8%Not measuredOnly Gemma 3 27B measured
Humanity's Last Exam (Artificial Analysis run)4.4%Not measuredOnly Gemma 3 27B measured
GPQA Diamond (Epoch AI run)47.7%Not measuredOnly Gemma 3 27B measured
LMArena Text: hard prompts1340Not measuredOnly Gemma 3 27B measured
LMArena Text: expert1304Not measuredOnly Gemma 3 27B measured
LMArena Text: hard prompts in English1353Not measuredOnly Gemma 3 27B measured
LMArena Vision: diagrams1156Not measuredOnly Gemma 3 27B measured
LMArena Vision: homework1160Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
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: math1312Not measuredOnly Gemma 3 27B measured
LMArena Text: mathematical work1327Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
MMLU Pro (Artificial Analysis run)66.9%Not measuredOnly Gemma 3 27B measured
GeoBench52.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: science1383Not measuredOnly Gemma 3 27B measured
LMArena Text: medicine and healthcare1391Not measuredOnly Gemma 3 27B measured
LMArena Text: legal and government1375Not measuredOnly Gemma 3 27B measured
LMArena Text: business and finance1360Not measuredOnly Gemma 3 27B measured
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 Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
General benchmarks for Gemma 3 27B and Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
IFBench31.8%Not measuredOnly Gemma 3 27B measured
Long context reasoning (AA-LCR)7.3%Not measuredOnly Gemma 3 27B measured
DTBench52.5%Not measuredOnly Gemma 3 27B measured
LMCA12.3%Not measuredOnly Gemma 3 27B measured
Fiction.LiveBench33.3%Not measuredOnly Gemma 3 27B measured
Creative writing (Lech Mazur)79.9%Not measuredOnly Gemma 3 27B measured
LMArena Text1358Not measuredOnly Gemma 3 27B measured
LMArena Text: instruction following1321Not measuredOnly Gemma 3 27B measured
LMArena Text: creative writing1345Not measuredOnly Gemma 3 27B measured
LMArena Vision1165Not measuredOnly Gemma 3 27B measured
LMArena Text: English1377Not measuredOnly Gemma 3 27B measured
LMArena Text: non-English1334Not measuredOnly Gemma 3 27B measured
LMArena Text: Chinese1346Not measuredOnly Gemma 3 27B measured
LMArena Text: German1362Not measuredOnly Gemma 3 27B measured
LMArena Text: Japanese1287Not measuredOnly Gemma 3 27B measured
LMArena Text: Korean1308Not measuredOnly Gemma 3 27B measured
LMArena Text: French1368Not measuredOnly Gemma 3 27B measured
LMArena Text: Spanish1349Not measuredOnly Gemma 3 27B measured
LMArena Text: Russian1349Not measuredOnly Gemma 3 27B measured
LMArena Text: Polish1345Not measuredOnly Gemma 3 27B measured
LMArena Text: multi-turn1345Not measuredOnly Gemma 3 27B measured
LMArena Text: longer queries1333Not measuredOnly Gemma 3 27B measured
LMArena Text: writing and language1347Not measuredOnly Gemma 3 27B measured
LMArena Text: entertainment and media1320Not measuredOnly Gemma 3 27B measured
LMArena Vision: English1188Not measuredOnly Gemma 3 27B measured
LMArena Vision: Chinese1164Not measuredOnly Gemma 3 27B measured
LMArena Vision: reading text1156Not measuredOnly Gemma 3 27B measured
LMArena Vision: humor1166Not measuredOnly Gemma 3 27B measured
LMArena Vision: captioning1151Not measuredOnly Gemma 3 27B measured
LMArena Vision: recognizing things1196Not measuredOnly Gemma 3 27B measured
LMArena Vision: creative writing1177Not measuredOnly Gemma 3 27B measured
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 Moondream 3 Preview
BenchmarkGemma 3 27BMoondream 3 PreviewLeader
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$0.0002Fits in one request
Moondream 3 Preview$0.0015Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Gemma 3 27B$0.0049Fits in one request
Moondream 3 Preview$0.022Exceeds the context window

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 27B$0.019Exceeds the context window
Moondream 3 Preview$0.085Exceeds the context window

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 Moondream 3 Preview
SpecificationGoogle Gemma 3 27BMoondream 3 Preview
MakerGoogleMoondream
WeightsOpen weightsOpen weights
ReleasedMarch 12, 2025October 15, 2026
Context window131K32K
Input $/Mtok$0.08$0.30
Output $/Mtok$0.30$2.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 27B better than Moondream 3 Preview for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Gemma 3 27B has the edge where output tokens cost 8.3x less, and where the context window is larger, 131K against 32K tokens.

Which is cheaper, Gemma 3 27B or Moondream 3 Preview?

Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; Moondream 3 Preview costs $0.30 and $2.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 3 27B or Moondream 3 Preview?

Gemma 3 27B, with 131K tokens against 32K.

How many benchmarks is the Gemma 3 27B vs Moondream 3 Preview comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Gemma 3 27B's coding index rests on 0 independent benchmarks and Moondream 3 Preview's on 0. Where only one model has a result, the page says so instead of naming a winner.

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