Gemma 4 26B A4B vs o3 Mini
Updated October 21, 2026. 38 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick o3 Mini for coding: it scores 52.1 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B.
Pick Gemma 4 26B A4B when output tokens cost 17.3x less, or when the context window is larger, 262K against 200K tokens.
- Shared results
- 38
- Gemma 4 26B A4B only
- 16
- o3 Mini only
- 32
- Like-for-like categories
- 7 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.
Coding
Vibe Coding Index, four public coding benchmarks
o3 Mini
o3 Mini scores 52.1 against 22.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemma 4 26B A4B
Gemma 4 26B A4B leads, 16.7 against 12.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemma 4 26B A4B has a AA Agentic Index result, 2.9.
Directional only
Reasoning
GPQA Diamond
No call
Only o3 Mini has a GPQA Diamond result, 75.5%.
Directional only
Math
AIME
No call
Only o3 Mini has a AIME result, 86.5%.
Directional only
Knowledge
MMLU Pro
No call
Only o3 Mini has a MMLU Pro result, 78.7%.
Directional only
Long documents
Listed context window
Gemma 4 26B A4B
Gemma 4 26B A4B takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0002, o3 Mini $0.0033 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B 22.8 from 1 benchmark, o3 Mini 52.1 from 2 benchmarks.
- Widest category
- Knowledge, 18.7 points apart on average over 4 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Gemma 4 26B A4B 65.7% against o3 Mini 43.0%, 22.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.255 against o3 Mini $4.40 per million output tokens, 17.3x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, o3 Mini 200K.
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 4 26B A4B | Bars | o3 Mini | Ties |
|---|---|---|---|---|
| Coding | 3 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 1 | ||
| Math | 3 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 17 | 0 | ||
| All shared boards | 35 | 3 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index32
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 60.4% | Only o3 Mini measured |
| SWE-bench Verified | Not measured | 42.4% | Only o3 Mini measured |
| SWE-bench Lite | Not measured | 32.3% | Only o3 Mini measured |
| LMArena WebDev | 1360 | Not measured | Only Gemma 4 26B A4B measured |
| AA Coding Index | 39.3 | Not measured | Only Gemma 4 26B A4B measured |
| LiveCodeBench (Vals AI) | Not measured | 71.5% | Only o3 Mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 73.4% | Only o3 Mini measured |
| SciCode | 40.0% | 42.8% | o3 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 6.8% | Gemma 4 26B A4B |
| GSO-Bench | Not measured | 1.3% | Only o3 Mini measured |
| WeirdML | 35.2% | 43.7% | o3 Mini |
| Cybench | Not measured | 22.5% | Only o3 Mini measured |
| ALE-Bench | 927.2 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: coding | 1446 | 1378 | Gemma 4 26B A4B |
| LMArena Text: software and IT | 1454 | 1364 | Gemma 4 26B A4B |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 12.5 | Gemma 4 26B A4B |
| Epoch Capabilities Index | 141.9 | 140.2 | Gemma 4 26B A4B |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| τ²-Bench Telecom | 43.6% | 31.3% | Gemma 4 26B A4B |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 75.5% | Only o3 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 77.3% | Gemma 4 26B A4B |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 12.0% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | 73.2% | 77.0% | o3 Mini |
| ARC-AGI | Not measured | 34.5% | Only o3 Mini measured |
| ARC-AGI-2 | Not measured | 3.0% | Only o3 Mini measured |
| SimpleBench | Not measured | 22.8% | Only o3 Mini measured |
| Chess puzzles | Not measured | 15.0% | Only o3 Mini measured |
| Mystery game puzzles | Not measured | 7.0% | Only o3 Mini measured |
| LMArena Text: hard prompts | 1438 | 1365 | Gemma 4 26B A4B |
| LMArena Text: expert | 1447 | 1364 | Gemma 4 26B A4B |
| LMArena Text: hard prompts in English | 1448 | 1375 | Gemma 4 26B A4B |
| LMArena Vision: diagrams | 1264 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: homework | 1293 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 86.5% | Only o3 Mini measured |
| MATH 500 (Vals AI) | Not measured | 91.8% | Only o3 Mini measured |
| MGSM (Vals AI) | Not measured | 91.3% | Only o3 Mini measured |
| OTIS Mock AIME | 82.2% | 76.9% | Gemma 4 26B A4B |
| FrontierMath, tiers 1 to 3 | Not measured | 18.6% | Only o3 Mini measured |
| FrontierMath, tier 4 | Not measured | 0.0% | Only o3 Mini measured |
| MATH level 5 | Not measured | 96.5% | Only o3 Mini measured |
| LMArena Text: math | 1470 | 1396 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1475 | 1399 | Gemma 4 26B A4B |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 78.7% | Only o3 Mini measured |
| LegalBench (Vals AI) | Not measured | 71.5% | Only o3 Mini measured |
| CorpFin (Vals AI) | Not measured | 45.3% | Only o3 Mini measured |
| TaxEval (Vals AI) | Not measured | 69.4% | Only o3 Mini measured |
| MedQA (Vals AI) | Not measured | 94.8% | Only o3 Mini measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.2% | Only o3 Mini measured |
| SimpleQA Verified | Not measured | 15.3% | Only o3 Mini measured |
| LMArena Text: science | 1446 | 1339 | Gemma 4 26B A4B |
| LMArena Text: medicine and healthcare | 1428 | 1330 | Gemma 4 26B A4B |
| LMArena Text: legal and government | 1457 | 1328 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1429 | 1313 | Gemma 4 26B A4B |
| Neither model has a result on the other 6 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
| Benchmark | Gemma 4 26B A4B | o3 Mini | Leader |
|---|---|---|---|
| IFBench | 72.4% | 67.1% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 65.7% | 43.0% | Gemma 4 26B A4B |
| DTBench | 74.9% | 68.8% | Gemma 4 26B A4B |
| LMCA | 29.7% | 19.0% | Gemma 4 26B A4B |
| Fiction.LiveBench | Not measured | 50.0% | Only o3 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 61.7% | Only o3 Mini measured |
| LMArena Text | 1434 | 1337 | Gemma 4 26B A4B |
| LMArena Text: instruction following | 1420 | 1337 | Gemma 4 26B A4B |
| LMArena Text: creative writing | 1400 | 1286 | Gemma 4 26B A4B |
| LMArena Vision | 1260 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1444 | 1351 | Gemma 4 26B A4B |
| LMArena Text: non-English | 1421 | 1319 | Gemma 4 26B A4B |
| LMArena Text: Chinese | 1495 | 1379 | Gemma 4 26B A4B |
| LMArena Text: German | Not measured | 1303 | Only o3 Mini measured |
| LMArena Text: Japanese | Not measured | 1286 | Only o3 Mini measured |
| LMArena Text: Korean | Not measured | 1313 | Only o3 Mini measured |
| LMArena Text: French | 1460 | 1334 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1415 | 1321 | Gemma 4 26B A4B |
| LMArena Text: Russian | 1434 | 1304 | Gemma 4 26B A4B |
| LMArena Text: Polish | Not measured | 1294 | Only o3 Mini measured |
| LMArena Text: multi-turn | 1441 | 1320 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1427 | 1343 | Gemma 4 26B A4B |
| LMArena Text: writing and language | 1405 | 1313 | Gemma 4 26B A4B |
| LMArena Text: entertainment and media | 1403 | 1283 | Gemma 4 26B A4B |
| LMArena Vision: English | 1256 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: Chinese | 1312 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: reading text | 1268 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: humor | 1272 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: captioning | 1297 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: recognizing things | 1191 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: creative writing | 1256 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | o3 Mini | 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 4 26B A4B costs less
Repository review
50K input + 3K output tokens
Gemma 4 26B A4B costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Google Gemma 4 26B A4B | OpenAI o3 Mini |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 3, 2026 | January 31, 2025 |
| Context window | 262K | 200K |
| Input $/Mtok | $0.0765 | $1.10 |
| Output $/Mtok | $0.255 | $4.40 |
| Coding index | 22.8 | 52.1 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B better than o3 Mini for coding?
Pick o3 Mini for coding: it scores 52.1 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B. Pick Gemma 4 26B A4B when output tokens cost 17.3x less, or when the context window is larger, 262K against 200K tokens.
Which is cheaper, Gemma 4 26B A4B or o3 Mini?
Gemma 4 26B A4B costs $0.0765 per million input tokens and $0.255 per million output tokens; o3 Mini costs $1.10 and $4.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 26B A4B or o3 Mini?
Gemma 4 26B A4B, with 262K tokens against 200K.
How many benchmarks is the Gemma 4 26B A4B vs o3 Mini comparison based on?
38 benchmarks have a result for both models as of October 21, 2026. Gemma 4 26B A4B's coding index rests on 1 independent benchmark and o3 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.