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Claude Haiku 5.5 vs Gemma 3 27B

Claude Haiku 5.5 leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 43.4 to 4.9, and Gemma 3 27B costs 1.7x less per output token ($0.30 vs $0.50 per million). Updated October 22, 2026; 10 benchmarks have a result for both.

Claude Haiku 5.5Anthropic
Coding
70.7
Overall
67.6
Output $/M
$0.50
10
Gemma 3 27BGoogle
Coding
No data
Overall
31.4
Output $/M
$0.30
0
vs boards won of 10 shared

Claude Haiku 5.5 or Gemma 3 27B: which to pick

Only Claude Haiku 5.5 has a coding score, 70.7 on the Vibe Coding Index; Gemma 3 27B has none, so the two cannot be ranked on coding.

Pick Gemma 3 27B for output tokens 1.7x cheaper ($0.30 vs $0.50 per million).

Shared results
10
Claude Haiku 5.5 only
53
Gemma 3 27B only
56
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
Claude Haiku 5.5 70.7 from 5 benchmarks, Gemma 3 27B not benchmarked.
Widest category
Math, 76.4 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: Claude Haiku 5.5 98.9% against Gemma 3 27B 22.5%, 76.4 points apart on a 0 to 100 scale.
Output price
Claude Haiku 5.5 $0.50 against Gemma 3 27B $0.30 per million output tokens, 1.7x apart.
Context window
Claude Haiku 5.5 takes 1M tokens, Gemma 3 27B 131K.

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
CategoryClaude Haiku 5.5BarsGemma 3 27BTies
Coding20
Intelligence20
Reasoning20
Math10
General30
All shared boards100
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
Aider polyglotNot measured4.9%Only Gemma 3 27B measured
LiveBench coding91.4%Not measuredOnly Claude Haiku 5.5 measured
LMArena WebDev1586Not measuredOnly Claude Haiku 5.5 measured
AA Coding IndexNot measured10.1Only Gemma 3 27B measured
Terminal-Bench 4 (Vals AI)36.4%Not measuredOnly Claude Haiku 5.5 measured
Vibe Code Bench (Vals AI)90.4%Not measuredOnly Claude Haiku 5.5 measured
Code migration (Vals AI)44.6%Not measuredOnly Claude Haiku 5.5 measured
ProgramBench (Vals AI)2.5%Not measuredOnly Claude Haiku 5.5 measured
IOI (Vals AI)47.3%Not measuredOnly Claude Haiku 5.5 measured
SWE-bench Multimodal (Vals AI)44.0%Not measuredOnly Claude Haiku 5.5 measured
Vibe Code Bench 1-100 (Vals AI)20.4%Not measuredOnly Claude Haiku 5.5 measured
CyberBench (Vals AI)75.5%Not measuredOnly Claude Haiku 5.5 measured
LiveCodeBench (Artificial Analysis run)Not measured13.7%Only Gemma 3 27B measured
SciCode55.0%23.3%Claude Haiku 5.5
Terminal-Bench Hard (Artificial Analysis run)Not measured3.8%Only Gemma 3 27B measured
FrontierCode46.4%Not measuredOnly Claude Haiku 5.5 measured
FrontierSWE43.8%Not measuredOnly Claude Haiku 5.5 measured
LMArena Text: codingNot measured1322Only Gemma 3 27B measured
LMArena Text: software and ITNot measured1354Only Gemma 3 27B measured
LMArena WebDev: React1605Not measuredOnly Claude Haiku 5.5 measured
LMArena WebDev: HTML1569Not measuredOnly Claude Haiku 5.5 measured
SciCode9.2%0.0%Claude Haiku 5.5
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
AA Intelligence Index43.44.9Claude Haiku 5.5
Epoch Capabilities Index159.3130.0Claude Haiku 5.5
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
Agentic work benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
AA Agentic IndexNot measured0.1Only Gemma 3 27B measured
LiveBench research81.9%Not measuredOnly Claude Haiku 5.5 measured
LiveBench browser80.0%Not measuredOnly Claude Haiku 5.5 measured
LiveBench long agentic57.6%Not measuredOnly Claude Haiku 5.5 measured
SREBench (Vals AI)5.7%Not measuredOnly Claude Haiku 5.5 measured
Finance Agent (Vals AI)54.1%Not measuredOnly Claude Haiku 5.5 measured
Tax Agent Bench (Vals AI)31.9%Not measuredOnly Claude Haiku 5.5 measured
Legal Research Bench (Vals AI)43.3%Not measuredOnly Claude Haiku 5.5 measured
Harvey's Legal Agent Benchmark (Vals AI)4.2%Not measuredOnly Claude Haiku 5.5 measured
Excel Modeling Benchmark (Vals AI)59.0%Not measuredOnly Claude Haiku 5.5 measured
BioMysteryBench (Vals AI)70.4%Not measuredOnly Claude Haiku 5.5 measured
Terminal-Bench-Science (Vals AI)10.0%Not measuredOnly Claude Haiku 5.5 measured
Vals Science Index38.5%Not measuredOnly Claude Haiku 5.5 measured
τ²-Bench TelecomNot measured10.5%Only Gemma 3 27B measured
APEX-Agents56.1%Not measuredOnly Claude Haiku 5.5 measured
Vending-Bench 2$3,602Not measuredOnly Claude Haiku 5.5 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured29.5%Only Gemma 3 27B measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
LiveBench reasoning82.4%Not measuredOnly Claude Haiku 5.5 measured
MysteryMechanism (Vals AI)35.1%Not measuredOnly Claude Haiku 5.5 measured
GPQA Diamond (Artificial Analysis run)Not measured42.8%Only Gemma 3 27B measured
Humanity's Last Exam (Artificial Analysis run)44.4%4.4%Claude Haiku 5.5
GPQA Diamond (Epoch AI run)89.6%47.7%Claude Haiku 5.5
ARC-AGI89.0%Not measuredOnly Claude Haiku 5.5 measured
ARC-AGI-261.3%Not measuredOnly Claude Haiku 5.5 measured
Chess puzzles55.0%Not measuredOnly Claude Haiku 5.5 measured
Mystery game puzzles30.0%Not measuredOnly Claude Haiku 5.5 measured
EBR-bench43.8%Not measuredOnly Claude Haiku 5.5 measured
LMArena Text: hard promptsNot measured1340Only Gemma 3 27B measured
LMArena Text: expertNot measured1304Only Gemma 3 27B measured
LMArena Text: hard prompts in EnglishNot measured1353Only Gemma 3 27B measured
LMArena Vision: diagramsNot measured1156Only Gemma 3 27B measured
LMArena Vision: homeworkNot measured1160Only Gemma 3 27B measured
Kagi LLM BenchmarkNot measured35.1%Only Gemma 3 27B measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
AA Math IndexNot measured20.7Only Gemma 3 27B measured
AIME 2025 (Artificial Analysis run)Not measured20.7%Only Gemma 3 27B measured
OTIS Mock AIME98.9%22.5%Claude Haiku 5.5
FrontierMath, tiers 1 to 375.1%Not measuredOnly Claude Haiku 5.5 measured
FrontierMath, tier 446.3%Not measuredOnly Claude Haiku 5.5 measured
ProofBench89.0%Not measuredOnly Claude Haiku 5.5 measured
MATH level 5Not measured74.0%Only Gemma 3 27B measured
LMArena Text: mathNot measured1312Only Gemma 3 27B measured
LMArena Text: mathematical workNot measured1327Only Gemma 3 27B measured
Neither model has a result on the other 4 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Knowledge benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
MedCode (Vals AI)51.5%Not measuredOnly Claude Haiku 5.5 measured
MMLU Pro (Artificial Analysis run)Not measured66.9%Only Gemma 3 27B measured
SimpleQA Verified23.8%Not measuredOnly Claude Haiku 5.5 measured
GeoBenchNot measured52.0%Only Gemma 3 27B measured
LMArena Text: scienceNot measured1383Only Gemma 3 27B measured
LMArena Text: medicine and healthcareNot measured1391Only Gemma 3 27B measured
LMArena Text: legal and governmentNot measured1375Only Gemma 3 27B measured
LMArena Text: business and financeNot measured1360Only Gemma 3 27B measured
FACTS Benchmark SuiteNot measured29.1%Only Gemma 3 27B measured
Neither model has a result on the other 9 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
Design Arena: websites1262Not measuredOnly Claude Haiku 5.5 measured
Design Arena: UI components1291Not measuredOnly Claude Haiku 5.5 measured
Design Arena: game dev1313Not measuredOnly Claude Haiku 5.5 measured
Design Arena: data viz1294Not measuredOnly Claude Haiku 5.5 measured
Design Arena: 3D1342Not measuredOnly Claude Haiku 5.5 measured
Design Arena: all code categories1278Not measuredOnly Claude Haiku 5.5 measured
LiveBench design83.1%Not measuredOnly Claude Haiku 5.5 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
General benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
Vals Index58.7%Not measuredOnly Claude Haiku 5.5 measured
LiveBench data analysis53.1%Not measuredOnly Claude Haiku 5.5 measured
Public Benefits Bench (Vals AI)63.2%Not measuredOnly Claude Haiku 5.5 measured
SAGE (Vals AI)45.8%Not measuredOnly Claude Haiku 5.5 measured
MedScribe (Vals AI)89.5%Not measuredOnly Claude Haiku 5.5 measured
IFBenchNot measured31.8%Only Gemma 3 27B measured
Long context reasoning (AA-LCR)82.7%7.3%Claude Haiku 5.5
DTBench95.0%52.5%Claude Haiku 5.5
LMCA51.1%12.3%Claude Haiku 5.5
Fiction.LiveBenchNot measured33.3%Only Gemma 3 27B measured
Creative writing (Lech Mazur)Not measured79.9%Only Gemma 3 27B measured
Furniture assembly47.5%Not measuredOnly Claude Haiku 5.5 measured
LMArena TextNot measured1358Only Gemma 3 27B measured
LMArena Text: instruction followingNot measured1321Only Gemma 3 27B measured
LMArena Text: creative writingNot measured1345Only Gemma 3 27B measured
LMArena VisionNot measured1165Only Gemma 3 27B measured
LMArena Text: EnglishNot measured1377Only Gemma 3 27B measured
LMArena Text: non-EnglishNot measured1334Only Gemma 3 27B measured
LMArena Text: ChineseNot measured1346Only Gemma 3 27B measured
LMArena Text: GermanNot measured1362Only Gemma 3 27B measured
LMArena Text: JapaneseNot measured1287Only Gemma 3 27B measured
LMArena Text: KoreanNot measured1308Only Gemma 3 27B measured
LMArena Text: FrenchNot measured1368Only Gemma 3 27B measured
LMArena Text: SpanishNot measured1349Only Gemma 3 27B measured
LMArena Text: RussianNot measured1349Only Gemma 3 27B measured
LMArena Text: PolishNot measured1345Only Gemma 3 27B measured
LMArena Text: multi-turnNot measured1345Only Gemma 3 27B measured
LMArena Text: longer queriesNot measured1333Only Gemma 3 27B measured
LMArena Text: writing and languageNot measured1347Only Gemma 3 27B measured
LMArena Text: entertainment and mediaNot measured1320Only Gemma 3 27B measured
LMArena Vision: EnglishNot measured1188Only Gemma 3 27B measured
LMArena Vision: ChineseNot measured1164Only Gemma 3 27B measured
LMArena Vision: reading textNot measured1156Only Gemma 3 27B measured
LMArena Vision: humorNot measured1166Only Gemma 3 27B measured
LMArena Vision: captioningNot measured1151Only Gemma 3 27B measured
LMArena Vision: recognizing thingsNot measured1196Only Gemma 3 27B measured
LMArena Vision: creative writingNot measured1177Only Gemma 3 27B measured
Neither model has a result on the other 9 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Haiku 5.5 and Gemma 3 27B
BenchmarkClaude Haiku 5.5Gemma 3 27BLeader
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

Claude Haiku 5.5$0.0003Fits in one request
Gemma 3 27B$0.0002Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Claude Haiku 5.5$0.0065Fits in one request
Gemma 3 27B$0.0049Fits in one request

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 5.5$0.025Fits in one request
Gemma 3 27B$0.019Exceeds 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 Claude Haiku 5.5 and Gemma 3 27B
SpecificationAnthropic Claude Haiku 5.5Google Gemma 3 27B
MakerAnthropicGoogle
WeightsNo public weights listedOpen weights
ReleasedOctober 7, 2026March 12, 2025
Context window1M131K
Input $/Mtok$0.10$0.08
Output $/Mtok$0.50$0.30
Coding index70.7Not benchmarked
Independent measurements behind it50
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Haiku 5.5 better than Gemma 3 27B for coding?

Only Claude Haiku 5.5 has a coding score, 70.7 on the Vibe Coding Index; Gemma 3 27B has none, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 1.7x cheaper ($0.30 vs $0.50 per million).

Which is cheaper, Claude Haiku 5.5 or Gemma 3 27B?

Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; Gemma 3 27B costs $0.08 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Claude Haiku 5.5 or Gemma 3 27B?

Claude Haiku 5.5, with 1M tokens against 131K.

How many benchmarks is the Claude Haiku 5.5 vs Gemma 3 27B comparison based on?

10 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 5.5's coding index rests on 5 independent benchmarks and Gemma 3 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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