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Gemma 2 27B vs Morph V3 Large

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 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
Morph V3 LargeMorph
Coding
No data
Overall
No data
Output $/M
$1.90
vs $0.65 vs $1.90 per 1M output tokens. Gemma 2 27B is 2.9x cheaper.

Decision reading

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

Gemma 2 27B has the edge where output tokens cost 2.9x less.

Shared results
0
Gemma 2 27B only
36
Morph V3 Large 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 2 27B not benchmarked, Morph V3 Large 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 2 27B $0.65 against Morph V3 Large $1.90 per million output tokens, 2.9x apart.
Context window
Gemma 2 27B takes 8K tokens, Morph V3 Large 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.

CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
Coding benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
LMArena Text: coding1211Not measuredOnly Gemma 2 27B measured
LMArena Text: software and IT1228Not measuredOnly Gemma 2 27B measured
Neither model has a result on the other 36 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
Epoch Capabilities Index122.1Not measuredOnly Gemma 2 27B measured
Neither model has a result on the other 1 board here
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
Neither model has a result on 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Reasoning benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
GPQA Diamond (Epoch AI run)36.5%Not measuredOnly Gemma 2 27B measured
LMArena Text: hard prompts1198Not measuredOnly Gemma 2 27B measured
LMArena Text: expert1171Not measuredOnly Gemma 2 27B measured
LMArena Text: hard prompts in English1206Not measuredOnly Gemma 2 27B measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
OTIS Mock AIME1.4%Not measuredOnly Gemma 2 27B measured
MATH level 527.9%Not measuredOnly Gemma 2 27B measured
LMArena Text: math1212Not measuredOnly Gemma 2 27B measured
LMArena Text: mathematical work1221Not measuredOnly Gemma 2 27B measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
LegalBench (Vals AI)68.0%Not measuredOnly Gemma 2 27B measured
MMLU75.7%Not measuredOnly Gemma 2 27B measured
LMArena Text: science1228Not measuredOnly Gemma 2 27B measured
LMArena Text: medicine and healthcare1198Not measuredOnly Gemma 2 27B measured
LMArena Text: legal and government1241Not measuredOnly Gemma 2 27B measured
LMArena Text: business and finance1208Not measuredOnly Gemma 2 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 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
General benchmarks for Gemma 2 27B and Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
DTBench48.0%Not measuredOnly Gemma 2 27B measured
LMCA7.1%Not measuredOnly Gemma 2 27B measured
LMArena Text1231Not measuredOnly Gemma 2 27B measured
LMArena Text: instruction following1206Not measuredOnly Gemma 2 27B measured
LMArena Text: creative writing1240Not measuredOnly Gemma 2 27B measured
LMArena Text: English1242Not measuredOnly Gemma 2 27B measured
LMArena Text: non-English1217Not measuredOnly Gemma 2 27B measured
LMArena Text: Chinese1221Not measuredOnly Gemma 2 27B measured
LMArena Text: German1209Not measuredOnly Gemma 2 27B measured
LMArena Text: Japanese1175Not measuredOnly Gemma 2 27B measured
LMArena Text: Korean1174Not measuredOnly Gemma 2 27B measured
LMArena Text: French1248Not measuredOnly Gemma 2 27B measured
LMArena Text: Spanish1228Not measuredOnly Gemma 2 27B measured
LMArena Text: Russian1234Not measuredOnly Gemma 2 27B measured
LMArena Text: Polish1277Not measuredOnly Gemma 2 27B measured
LMArena Text: multi-turn1224Not measuredOnly Gemma 2 27B measured
LMArena Text: longer queries1230Not measuredOnly Gemma 2 27B measured
LMArena Text: writing and language1249Not measuredOnly Gemma 2 27B measured
LMArena Text: entertainment and media1212Not measuredOnly Gemma 2 27B measured
Neither model has a result on the other 27 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 Morph V3 Large
BenchmarkGemma 2 27BMorph V3 LargeLeader
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
Morph V3 Large$0.0019Fits in one request

Gemma 2 27B costs less

Repository review

50K input + 3K output tokens

Gemma 2 27B$0.034Exceeds the context window
Morph V3 Large$0.051Fits in one request

Gemma 2 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 2 27B$0.137Exceeds the context window
Morph V3 Large$0.199Fits in one request

Gemma 2 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 2 27B and Morph V3 Large
SpecificationGoogle Gemma 2 27BMorph V3 Large
MakerGoogleMorph
WeightsOpen weightsNo public weights listed
ReleasedJuly 13, 2024July 7, 2025
Context window8K262K
Input $/Mtok$0.65$0.90
Output $/Mtok$0.65$1.90
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 2 27B better than Morph V3 Large for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Gemma 2 27B has the edge where output tokens cost 2.9x less.

Which is cheaper, Gemma 2 27B or Morph V3 Large?

Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; Morph V3 Large costs $0.90 and $1.90. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 2 27B or Morph V3 Large?

Morph V3 Large, with 262K tokens against 8K.

How many benchmarks is the Gemma 2 27B vs Morph V3 Large comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Gemma 2 27B's coding index rests on 0 independent benchmarks and Morph V3 Large's on 0. Where only one model has a result, the page says so instead of naming a winner.

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