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Gemma 4 26B A4B vs GPT-5 Mini

GPT-5 Mini leads Gemma 4 26B A4B on the Artificial Analysis Intelligence Index, 20.6 to 16.7, and Gemma 4 26B A4B costs 3.3x less per output token ($0.60 vs $2.00 per million). Updated October 22, 2026; 49 benchmarks have a result for both.

Replace Gemma 4 26B A4B Replace GPT-5 Mini
Gemma 4 26B A4BGoogle
Coding
No data
Overall
54.7
Output $/M
$0.60
35
GPT-5 MiniOpenAI
Coding
34.2
Overall
43.7
Output $/M
$2.00
14
vs boards won of 49 shared

Gemma 4 26B A4B or GPT-5 Mini: which to pick

Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Gemma 4 26B A4B has none, so the two cannot be ranked on coding.

Pick Gemma 4 26B A4B for output tokens 3.3x cheaper ($0.60 vs $2.00 per million) and work measured by SciCode or LMArena Text: coding, where it leads.

Model AGemma 4 26B A4BGoogleNot benchmarked1 independent benchmarkNo cost per solved taskModel BGPT-5 MiniOpenAI34.2/1002 independent benchmarks$0.08 per solved task
Shared results
49
Gemma 4 26B A4B only
6
GPT-5 Mini only
52
Like-for-like categories
7 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 4 26B A4B not benchmarked, GPT-5 Mini 34.2 from 2 benchmarks.
Widest category
Agentic work, 27.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against GPT-5 Mini 71.1%, 27.5 points apart on a 0 to 100 scale.
Output price
Gemma 4 26B A4B $0.60 against GPT-5 Mini $2.00 per million output tokens, 3.3x apart.
Context window
Gemma 4 26B A4B takes 262K tokens, GPT-5 Mini 400K.

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 4 26B A4BBarsGPT-5 MiniTies
Coding32
Intelligence02
Agentic work01
Reasoning53
Math21
Knowledge50
General205
All shared boards3514
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
SWE-bench VerifiedNot measured59.8%Only GPT-5 Mini measured
SWE-bench MultilingualNot measured39.7%Only GPT-5 Mini measured
LMArena WebDev1360Not measuredOnly Gemma 4 26B A4B measured
AA Coding Index39.3Not measuredOnly Gemma 4 26B A4B measured
LiveCodeBench (Vals AI)Not measured86.6%Only GPT-5 Mini measured
SWE-bench Verified (Vals AI)Not measured60.8%Only GPT-5 Mini measured
Vibe Code Bench (Vals AI)Not measured14.2%Only GPT-5 Mini measured
LiveCodeBench (Artificial Analysis run)Not measured83.8%Only GPT-5 Mini measured
SciCode40.0%39.0%Gemma 4 26B A4B
Terminal-Bench Hard (Artificial Analysis run)25.0%33.3%GPT-5 Mini
Terminal-BenchNot measured34.8%Only GPT-5 Mini measured
WeirdML35.2%52.7%GPT-5 Mini
ALE-Bench927.2Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: coding14461406Gemma 4 26B A4B
LMArena Text: software and IT14541394Gemma 4 26B A4B
LMArena WebDev: React1351Not measuredOnly Gemma 4 26B A4B measured
LMArena WebDev: HTML1362Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
AA Intelligence Index16.720.6GPT-5 Mini
Epoch Capabilities Index141.9145.3GPT-5 Mini
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
AA Agentic Index2.9Not measuredOnly Gemma 4 26B A4B measured
τ²-Bench Telecom43.6%71.1%GPT-5 Mini
Vending-Bench 2Not measured-$31Only GPT-5 Mini measured
Berkeley Function Calling Leaderboard (BFCL)Not measured55.5%Only GPT-5 Mini measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index53
Reasoning benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
GPQA DiamondNot measured80.3%Only GPT-5 Mini measured
MMMU Pro (Vals AI)Not measured78.9%Only GPT-5 Mini measured
GPQA Diamond (Artificial Analysis run)79.2%82.8%GPT-5 Mini
Humanity's Last Exam (Artificial Analysis run)19.3%21.5%GPT-5 Mini
GPQA Diamond (Epoch AI run)73.2%75.0%GPT-5 Mini
ARC-AGINot measured54.3%Only GPT-5 Mini measured
ARC-AGI-2Not measured4.4%Only GPT-5 Mini measured
Chess puzzlesNot measured24.0%Only GPT-5 Mini measured
Mystery game puzzlesNot measured10.0%Only GPT-5 Mini measured
VPCTNot measured40.2%Only GPT-5 Mini measured
LMArena Text: hard prompts14381380Gemma 4 26B A4B
LMArena Text: expert14471379Gemma 4 26B A4B
LMArena Text: hard prompts in English14481383Gemma 4 26B A4B
LMArena Vision: diagrams12641202Gemma 4 26B A4B
LMArena Vision: homework12931210Gemma 4 26B A4B
Kagi LLM BenchmarkNot measured70.3%Only GPT-5 Mini measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
AIMENot measured91.5%Only GPT-5 Mini measured
MATH 500 (Vals AI)Not measured94.8%Only GPT-5 Mini measured
MGSM (Vals AI)Not measured92.6%Only GPT-5 Mini measured
AA Math IndexNot measured90.7Only GPT-5 Mini measured
AIME 2025 (Artificial Analysis run)Not measured90.7%Only GPT-5 Mini measured
OTIS Mock AIME82.2%86.7%GPT-5 Mini
FrontierMath, tiers 1 to 3Not measured46.7%Only GPT-5 Mini measured
FrontierMath, tier 4Not measured12.2%Only GPT-5 Mini measured
ProofBenchNot measured9.0%Only GPT-5 Mini measured
MATH level 5Not measured97.8%Only GPT-5 Mini measured
LMArena Text: math14701378Gemma 4 26B A4B
LMArena Text: mathematical work14751380Gemma 4 26B A4B
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
MMLU ProNot measured82.2%Only GPT-5 Mini measured
LegalBench (Vals AI)Not measured81.8%Only GPT-5 Mini measured
CaseLaw (Vals AI)Not measured68.5%Only GPT-5 Mini measured
CorpFin (Vals AI)Not measured60.2%Only GPT-5 Mini measured
TaxEval (Vals AI)Not measured75.2%Only GPT-5 Mini measured
MortgageTax (Vals AI)Not measured66.9%Only GPT-5 Mini measured
MedQA (Vals AI)Not measured96.1%Only GPT-5 Mini measured
MedCode (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MMLU Pro (Artificial Analysis run)Not measured83.7%Only GPT-5 Mini measured
SimpleQA VerifiedNot measured21.6%Only GPT-5 Mini measured
LMArena Text: science14461371Gemma 4 26B A4B
LMArena Text: medicine and healthcare14281380Gemma 4 26B A4B
LMArena Text: legal and government14571375Gemma 4 26B A4B
LMArena Text: business and finance14291358Gemma 4 26B A4B
FACTS Benchmark Suite42.7%38.6%Gemma 4 26B A4B
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
Design Arena: websitesNot measured1125Only GPT-5 Mini measured
Design Arena: UI componentsNot measured1103Only GPT-5 Mini measured
Design Arena: game devNot measured1129Only GPT-5 Mini measured
Design Arena: data vizNot measured1131Only GPT-5 Mini measured
Design Arena: 3DNot measured1036Only GPT-5 Mini measured
Design Arena: all code categoriesNot measured1114Only GPT-5 Mini measured
Design Arena: SVGNot measured1091Only GPT-5 Mini measured
Design Arena: ASCII artNot measured1125Only GPT-5 Mini measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index205
General benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
SAGE (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MedScribe (Vals AI)Not measured80.6%Only GPT-5 Mini measured
IFBench72.4%75.4%GPT-5 Mini
Long context reasoning (AA-LCR)65.7%72.3%GPT-5 Mini
DTBench74.9%80.5%GPT-5 Mini
LMCA29.7%34.2%GPT-5 Mini
Fiction.LiveBenchNot measured69.4%Only GPT-5 Mini measured
Creative writing (Lech Mazur)Not measured83.1%Only GPT-5 Mini measured
LMArena Text14341373Gemma 4 26B A4B
LMArena Text: instruction following14201357Gemma 4 26B A4B
LMArena Text: creative writing14001325Gemma 4 26B A4B
LMArena Vision12601202Gemma 4 26B A4B
LMArena Text: English14441379Gemma 4 26B A4B
LMArena Text: non-English14211363Gemma 4 26B A4B
LMArena Text: Chinese14951386Gemma 4 26B A4B
LMArena Text: GermanNot measured1366Only GPT-5 Mini measured
LMArena Text: JapaneseNot measured1341Only GPT-5 Mini measured
LMArena Text: KoreanNot measured1308Only GPT-5 Mini measured
LMArena Text: French14601386Gemma 4 26B A4B
LMArena Text: Spanish14151354Gemma 4 26B A4B
LMArena Text: Russian14341362Gemma 4 26B A4B
LMArena Text: PolishNot measured1378Only GPT-5 Mini measured
LMArena Text: multi-turn14411363Gemma 4 26B A4B
LMArena Text: longer queries14271355Gemma 4 26B A4B
LMArena Text: writing and language14051344Gemma 4 26B A4B
LMArena Text: entertainment and media14031340Gemma 4 26B A4B
LMArena Vision: English12561216Gemma 4 26B A4B
LMArena Vision: Chinese13121214Gemma 4 26B A4B
LMArena Vision: reading text12681199Gemma 4 26B A4B
LMArena Vision: humor12721205Gemma 4 26B A4B
LMArena Vision: captioning12971217Gemma 4 26B A4B
LMArena Vision: recognizing things11911226GPT-5 Mini
LMArena Vision: creative writing12561181Gemma 4 26B A4B
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 26B A4B and GPT-5 Mini
BenchmarkGemma 4 26B A4BGPT-5 MiniLeader
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 4 26B A4B$0.0004Fits in one request
GPT-5 Mini$0.0013Fits in one request

Gemma 4 26B A4B costs less

Repository review

50K input + 3K output tokens

Gemma 4 26B A4B$0.0093Fits in one request
GPT-5 Mini$0.018Fits in one request

Gemma 4 26B A4B costs less

Agent loop

200K input + 10K output tokens

Gemma 4 26B A4B$0.036Fits in one request
GPT-5 Mini$0.070Fits in one request

Gemma 4 26B A4B 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 4 26B A4B and GPT-5 Mini
SpecificationGoogle Gemma 4 26B A4BOpenAI GPT-5 Mini
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 3, 2026August 7, 2025
Context window262K400K
Input $/Mtok$0.15$0.25
Output $/Mtok$0.60$2.00
Coding indexNot benchmarked34.2
Independent measurements behind it12
Cost per solved taskNot computable$0.08
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 26B A4B better than GPT-5 Mini for coding?

Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Gemma 4 26B A4B has none, so the two cannot be ranked on coding. Pick Gemma 4 26B A4B for output tokens 3.3x cheaper ($0.60 vs $2.00 per million) and work measured by SciCode or LMArena Text: coding, where it leads.

Which is cheaper, Gemma 4 26B A4B or GPT-5 Mini?

Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5 Mini costs $0.25 and $2.00. Cost per solved task is known for GPT-5 Mini only.

Which has the bigger context window, Gemma 4 26B A4B or GPT-5 Mini?

GPT-5 Mini, with 400K tokens against 262K.

How many benchmarks is the Gemma 4 26B A4B vs GPT-5 Mini comparison based on?

49 benchmarks have a result for both models as of October 22, 2026. Gemma 4 26B A4B's coding index rests on 1 independent benchmark and GPT-5 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.

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