Gemma 3 27B vs Llama 4 Maverick
Llama 4 Maverick leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 9.3 to 4.9, and Gemma 3 27B costs 3.3x less per output token ($0.30 vs $1.00 per million). Updated October 22, 2026; 58 benchmarks have a result for both.
Gemma 3 27B or Llama 4 Maverick: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 3 27B for output tokens 3.3x cheaper ($0.30 vs $1.00 per million) and work measured by Aider polyglot or AA Coding Index, where it leads.
- Shared results
- 58
- Gemma 3 27B only
- 8
- Llama 4 Maverick only
- 27
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Llama 4 Maverick
Llama 4 Maverick leads, 9.3 against 4.9.
Same board, both measured
Agentic work
AA Agentic Index
Llama 4 Maverick
Llama 4 Maverick leads, 0.6 against 0.1.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Llama 4 Maverick has a GPQA Diamond result, 69.4%.
Directional only
Math
AIME
No call
Only Llama 4 Maverick has a AIME result, 25.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Llama 4 Maverick has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
No call
Only Llama 4 Maverick has a Design Arena: websites result, 871.
Directional only
Long documents
Listed context window
Llama 4 Maverick
Llama 4 Maverick takes 524K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 27B
Gemma 3 27B $0.0002, Llama 4 Maverick $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Llama 4 Maverick has the number, $1.491.
Directional only
At a glance
- Coding index
- Gemma 3 27B not benchmarked, Llama 4 Maverick not benchmarked.
- Widest category
- Knowledge, 13.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Gemma 3 27B 7.3% against Llama 4 Maverick 50.0%, 42.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 27B $0.30 against Llama 4 Maverick $1.00 per million output tokens, 3.3x apart.
- Context window
- Gemma 3 27B takes 131K tokens, Llama 4 Maverick 524K.
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.
| Category | Gemma 3 27B | Bars | Llama 4 Maverick | Ties |
|---|---|---|---|---|
| Coding | 2 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 4 | 4 | ||
| Math | 4 | 0 | ||
| Knowledge | 4 | 1 | 1 tie | |
| General | 24 | 5 | ||
| All shared boards | 38 | 19 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index25
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| Aider polyglot | 4.9% | 15.6% | Llama 4 Maverick |
| SWE-bench Verified | Not measured | 21.0% | Only Llama 4 Maverick measured |
| AA Coding Index | 10.1 | 16.3 | Llama 4 Maverick |
| LiveCodeBench (Vals AI) | Not measured | 47.3% | Only Llama 4 Maverick measured |
| LiveCodeBench (Artificial Analysis run) | 13.7% | 39.7% | Llama 4 Maverick |
| SciCode | 23.3% | 31.7% | Llama 4 Maverick |
| Terminal-Bench Hard (Artificial Analysis run) | 3.8% | 6.8% | Llama 4 Maverick |
| WeirdML | Not measured | 24.5% | Only Llama 4 Maverick measured |
| ALE-Bench | Not measured | 173.0 | Only Llama 4 Maverick measured |
| LMArena Text: coding | 1322 | 1301 | Gemma 3 27B |
| LMArena Text: software and IT | 1354 | 1299 | Gemma 3 27B |
| SciCode | 0.0% | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| AA Intelligence Index | 4.9 | 9.3 | Llama 4 Maverick |
| Epoch Capabilities Index | 130.0 | 132.2 | Llama 4 Maverick |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| AA Agentic Index | 0.1 | 0.6 | Llama 4 Maverick |
| τ²-Bench Telecom | 10.5% | 17.8% | Llama 4 Maverick |
| Berkeley Function Calling Leaderboard (BFCL) | 29.5% | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 69.4% | Only Llama 4 Maverick measured |
| MMMU Pro (Vals AI) | Not measured | 71.7% | Only Llama 4 Maverick measured |
| GPQA Diamond (Artificial Analysis run) | 42.8% | 67.1% | Llama 4 Maverick |
| Humanity's Last Exam (Artificial Analysis run) | 4.4% | 4.9% | Llama 4 Maverick |
| GPQA Diamond (Epoch AI run) | 47.7% | Not measured | Only Gemma 3 27B measured |
| ARC-AGI | Not measured | 4.4% | Only Llama 4 Maverick measured |
| ARC-AGI-2 | Not measured | 0.0% | Only Llama 4 Maverick measured |
| SimpleBench | Not measured | 27.7% | Only Llama 4 Maverick measured |
| LMArena Text: hard prompts | 1340 | 1281 | Gemma 3 27B |
| LMArena Text: expert | 1304 | 1259 | Gemma 3 27B |
| LMArena Text: hard prompts in English | 1353 | 1295 | Gemma 3 27B |
| LMArena Vision: diagrams | 1156 | 1134 | Gemma 3 27B |
| LMArena Vision: homework | 1160 | 1164 | Llama 4 Maverick |
| Kagi LLM Benchmark | 35.1% | 55.9% | Llama 4 Maverick |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| AIME | Not measured | 25.2% | Only Llama 4 Maverick measured |
| MATH 500 (Vals AI) | Not measured | 85.2% | Only Llama 4 Maverick measured |
| MGSM (Vals AI) | Not measured | 92.4% | Only Llama 4 Maverick measured |
| AA Math Index | 20.7 | 19.3 | Gemma 3 27B |
| AIME 2025 (Artificial Analysis run) | 20.7% | 19.3% | Gemma 3 27B |
| OTIS Mock AIME | 22.5% | Not measured | Only Gemma 3 27B measured |
| MATH level 5 | 74.0% | Not measured | Only Gemma 3 27B measured |
| LMArena Text: math | 1312 | 1299 | Gemma 3 27B |
| LMArena Text: mathematical work | 1327 | 1295 | Gemma 3 27B |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.4% | Only Llama 4 Maverick measured |
| LegalBench (Vals AI) | Not measured | 77.8% | Only Llama 4 Maverick measured |
| CorpFin (Vals AI) | Not measured | 49.7% | Only Llama 4 Maverick measured |
| TaxEval (Vals AI) | Not measured | 66.6% | Only Llama 4 Maverick measured |
| MortgageTax (Vals AI) | Not measured | 58.5% | Only Llama 4 Maverick measured |
| MedQA (Vals AI) | Not measured | 43.3% | Only Llama 4 Maverick measured |
| MedCode (Vals AI) | Not measured | 36.5% | Only Llama 4 Maverick measured |
| MMLU Pro (Artificial Analysis run) | 66.9% | 80.9% | Llama 4 Maverick |
| GeoBench | 52.0% | 52.0% | Tie |
| LMArena Text: science | 1383 | 1288 | Gemma 3 27B |
| LMArena Text: medicine and healthcare | 1391 | 1275 | Gemma 3 27B |
| LMArena Text: legal and government | 1375 | 1286 | Gemma 3 27B |
| LMArena Text: business and finance | 1360 | 1260 | Gemma 3 27B |
| FACTS Benchmark Suite | 29.1% | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 871 | Only Llama 4 Maverick measured |
| Design Arena: UI components | Not measured | 896 | Only Llama 4 Maverick measured |
| Design Arena: game dev | Not measured | 837 | Only Llama 4 Maverick measured |
| Design Arena: data viz | Not measured | 882 | Only Llama 4 Maverick measured |
| Design Arena: 3D | Not measured | 900 | Only Llama 4 Maverick measured |
| Design Arena: all code categories | Not measured | 879 | Only Llama 4 Maverick measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index245
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 35.7% | Only Llama 4 Maverick measured |
| MedScribe (Vals AI) | Not measured | 54.2% | Only Llama 4 Maverick measured |
| IFBench | 31.8% | 43.0% | Llama 4 Maverick |
| Long context reasoning (AA-LCR) | 7.3% | 50.0% | Llama 4 Maverick |
| DTBench | 52.5% | 61.9% | Llama 4 Maverick |
| LMCA | 12.3% | 15.9% | Llama 4 Maverick |
| Fiction.LiveBench | 33.3% | 46.2% | Llama 4 Maverick |
| Creative writing (Lech Mazur) | 79.9% | 62.0% | Gemma 3 27B |
| LMArena Text | 1358 | 1287 | Gemma 3 27B |
| LMArena Text: instruction following | 1321 | 1267 | Gemma 3 27B |
| LMArena Text: creative writing | 1345 | 1266 | Gemma 3 27B |
| LMArena Vision | 1165 | 1142 | Gemma 3 27B |
| LMArena Text: English | 1377 | 1303 | Gemma 3 27B |
| LMArena Text: non-English | 1334 | 1269 | Gemma 3 27B |
| LMArena Text: Chinese | 1346 | 1277 | Gemma 3 27B |
| LMArena Text: German | 1362 | 1291 | Gemma 3 27B |
| LMArena Text: Japanese | 1287 | 1206 | Gemma 3 27B |
| LMArena Text: Korean | 1308 | 1203 | Gemma 3 27B |
| LMArena Text: French | 1368 | 1259 | Gemma 3 27B |
| LMArena Text: Spanish | 1349 | 1293 | Gemma 3 27B |
| LMArena Text: Russian | 1349 | 1286 | Gemma 3 27B |
| LMArena Text: Polish | 1345 | 1275 | Gemma 3 27B |
| LMArena Text: multi-turn | 1345 | 1289 | Gemma 3 27B |
| LMArena Text: longer queries | 1333 | 1280 | Gemma 3 27B |
| LMArena Text: writing and language | 1347 | 1277 | Gemma 3 27B |
| LMArena Text: entertainment and media | 1320 | 1250 | Gemma 3 27B |
| LMArena Vision: English | 1188 | 1150 | Gemma 3 27B |
| LMArena Vision: Chinese | 1164 | 1141 | Gemma 3 27B |
| LMArena Vision: reading text | 1156 | 1143 | Gemma 3 27B |
| LMArena Vision: humor | 1166 | 1100 | Gemma 3 27B |
| LMArena Vision: captioning | 1151 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: recognizing things | 1196 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: creative writing | 1177 | 1099 | Gemma 3 27B |
| 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
| Benchmark | Gemma 3 27B | Llama 4 Maverick | Leader |
|---|---|---|---|
| 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 costs less
Repository review
50K input + 3K output tokens
Gemma 3 27B costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Google Gemma 3 27B | Meta Llama 4 Maverick |
|---|---|---|
| Maker | Meta Llama | |
| Weights | Open weights | Open weights |
| Released | March 12, 2025 | April 5, 2025 |
| Context window | 131K | 524K |
| Input $/Mtok | $0.08 | $0.35 |
| Output $/Mtok | $0.30 | $1.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | $1.491 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 3 27B better than Llama 4 Maverick for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 3.3x cheaper ($0.30 vs $1.00 per million) and work measured by Aider polyglot or AA Coding Index, where it leads.
Which is cheaper, Gemma 3 27B or Llama 4 Maverick?
Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; Llama 4 Maverick costs $0.35 and $1.00. Cost per solved task is known for Llama 4 Maverick only.
Which has the bigger context window, Gemma 3 27B or Llama 4 Maverick?
Llama 4 Maverick, with 524K tokens against 131K.
How many benchmarks is the Gemma 3 27B vs Llama 4 Maverick comparison based on?
58 benchmarks have a result for both models as of October 22, 2026. Gemma 3 27B's coding index rests on 0 independent benchmarks and Llama 4 Maverick's on 0. Where only one model has a result, the page says so instead of naming a winner.