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Gemma 2 27B vs GLM 5

Updated October 21, 2026. 32 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemma 2 27B Replace GLM 5
Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
0
GLM 5Z.ai
Coding
41.7
Overall
27.9
Output $/M
$3.20
32
vs boards won of 32 shared

Decision reading

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding.

Gemma 2 27B has the edge where output tokens cost 4.9x less.

Model AGemma 2 27BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 5Z.ai41.7/1003 independent benchmarks$0.63 per solved task
Shared results
32
Gemma 2 27B only
4
GLM 5 only
43
Like-for-like categories
6 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, GLM 5 41.7 from 3 benchmarks.
Widest category
Math, 51.6 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: Gemma 2 27B 1.4% against GLM 5 80.0%, 78.6 points apart on a 0 to 100 scale.
Output price
Gemma 2 27B $0.65 against GLM 5 $3.20 per million output tokens, 4.9x apart.
Context window
Gemma 2 27B takes 8K tokens, GLM 5 205K.

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 27BBarsGLM 5Ties
Coding02
Intelligence01
Reasoning04
Math03
Knowledge05
General017
All shared boards032
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
SWE-bench VerifiedNot measured72.8%Only GLM 5 measured
SWE-bench MultilingualNot measured69.7%Only GLM 5 measured
LMArena WebDevNot measured1435Only GLM 5 measured
LiveCodeBench (Vals AI)Not measured81.9%Only GLM 5 measured
SWE-bench Verified (Vals AI)Not measured71.4%Only GLM 5 measured
Vibe Code Bench (Vals AI)Not measured23.4%Only GLM 5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured43.2%Only GLM 5 measured
Terminal-BenchNot measured52.4%Only GLM 5 measured
WeirdMLNot measured48.2%Only GLM 5 measured
ALE-BenchNot measured765.6Only GLM 5 measured
LMArena Text: coding12111461GLM 5
LMArena Text: software and IT12281460GLM 5
LMArena WebDev: ReactNot measured1424Only GLM 5 measured
LMArena WebDev: HTMLNot measured1450Only GLM 5 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
AA Intelligence IndexNot measured27.9Only GLM 5 measured
Epoch Capabilities Index122.1145.8GLM 5
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
Design Arena: agents building full-stack appsNot measured1123Only GLM 5 measured
Design Arena: agents building mobile appsNot measured1136Only GLM 5 measured
Design Arena: agents building Android appsNot measured1153Only GLM 5 measured
Design Arena: agents building Godot gamesNot measured1144Only GLM 5 measured
Design Arena: HTML slidesNot measured1148Only GLM 5 measured
τ²-Bench TelecomNot measured98.2%Only GLM 5 measured
Vending-Bench 2Not measured$4,432Only GLM 5 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
GPQA DiamondNot measured83.3%Only GLM 5 measured
GPQA Diamond (Artificial Analysis run)Not measured82.0%Only GLM 5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured29.3%Only GLM 5 measured
GPQA Diamond (Epoch AI run)36.5%87.8%GLM 5
ARC-AGINot measured44.7%Only GLM 5 measured
ARC-AGI-2Not measured4.9%Only GLM 5 measured
SimpleBenchNot measured53.2%Only GLM 5 measured
LMArena Text: hard prompts11981452GLM 5
LMArena Text: expert11711454GLM 5
LMArena Text: hard prompts in English12061460GLM 5
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
AIMENot measured91.7%Only GLM 5 measured
OTIS Mock AIME1.4%80.0%GLM 5
MATH level 527.9%Not measuredOnly Gemma 2 27B measured
LMArena Text: math12121440GLM 5
LMArena Text: mathematical work12211451GLM 5
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
MMLU ProNot measured86.0%Only GLM 5 measured
LegalBench (Vals AI)68.0%84.1%GLM 5
CaseLaw (Vals AI)Not measured52.5%Only GLM 5 measured
CorpFin (Vals AI)Not measured62.9%Only GLM 5 measured
TaxEval (Vals AI)Not measured70.0%Only GLM 5 measured
MedQA (Vals AI)Not measured94.3%Only GLM 5 measured
MMLU75.7%Not measuredOnly Gemma 2 27B measured
LMArena Text: science12281460GLM 5
LMArena Text: medicine and healthcare11981455GLM 5
LMArena Text: legal and government12411453GLM 5
LMArena Text: business and finance12081430GLM 5
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
Design Arena: websitesNot measured1247Only GLM 5 measured
Design Arena: UI componentsNot measured1230Only GLM 5 measured
Design Arena: game devNot measured1234Only GLM 5 measured
Design Arena: data vizNot measured1228Only GLM 5 measured
Design Arena: 3DNot measured1229Only GLM 5 measured
Design Arena: all code categoriesNot measured1246Only GLM 5 measured
Design Arena: SVGNot measured1168Only GLM 5 measured
Design Arena: ASCII artNot measured1146Only GLM 5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for Gemma 2 27B and GLM 5
BenchmarkGemma 2 27BGLM 5Leader
IFBenchNot measured72.3%Only GLM 5 measured
Long context reasoning (AA-LCR)Not measured75.7%Only GLM 5 measured
DTBench48.0%Not measuredOnly Gemma 2 27B measured
LMCA7.1%Not measuredOnly Gemma 2 27B measured
CL-benchNot measured18.7%Only GLM 5 measured
LMArena Text12311446GLM 5
LMArena Text: instruction following12061428GLM 5
LMArena Text: creative writing12401438GLM 5
LMArena Text: English12421458GLM 5
LMArena Text: non-English12171430GLM 5
LMArena Text: Chinese12211511GLM 5
LMArena Text: German12091447GLM 5
LMArena Text: Japanese11751416GLM 5
LMArena Text: Korean11741423GLM 5
LMArena Text: French12481456GLM 5
LMArena Text: Spanish12281454GLM 5
LMArena Text: Russian12341436GLM 5
LMArena Text: Polish12771434GLM 5
LMArena Text: multi-turn12241456GLM 5
LMArena Text: longer queries12301446GLM 5
LMArena Text: writing and language12491437GLM 5
LMArena Text: entertainment and media12121426GLM 5
Neither model has a result on the other 24 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 GLM 5
BenchmarkGemma 2 27BGLM 5Leader
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
GLM 5$0.0026Fits in one request

Gemma 2 27B costs less

Repository review

50K input + 3K output tokens

Gemma 2 27B$0.034Exceeds the context window
GLM 5$0.060Fits in one request

Gemma 2 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 2 27B$0.137Exceeds the context window
GLM 5$0.232Exceeds the context window

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 GLM 5
SpecificationGoogle Gemma 2 27BZ.ai GLM 5
MakerGoogleZ.ai
WeightsOpen weightsOpen weights
ReleasedJuly 13, 2024February 11, 2026
Context window8K205K
Input $/Mtok$0.65$1.00
Output $/Mtok$0.65$3.20
Coding indexNot benchmarked41.7
Independent measurements behind it03
Cost per solved taskNot computable$0.63
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 2 27B better than GLM 5 for coding?

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding. Gemma 2 27B has the edge where output tokens cost 4.9x less.

Which is cheaper, Gemma 2 27B or GLM 5?

Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; GLM 5 costs $1.00 and $3.20. Cost per solved task is known for GLM 5 only.

Which has the bigger context window, Gemma 2 27B or GLM 5?

GLM 5, with 205K tokens against 8K.

How many benchmarks is the Gemma 2 27B vs GLM 5 comparison based on?

32 benchmarks have a result for both models as of October 21, 2026. Gemma 2 27B's coding index rests on 0 independent benchmarks and GLM 5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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