Gemma 4 26B A4B vs GPT-4o-mini
Gemma 4 26B A4B leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 16.7 to 6.7, at about the same output price ($0.60 vs $0.60 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
Gemma 4 26B A4B or GPT-4o-mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 4 26B A4B for a larger context window (262K against 128K tokens).
- Shared results
- 8
- Gemma 4 26B A4B only
- 47
- GPT-4o-mini only
- 21
- Like-for-like categories
- 4 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
Gemma 4 26B A4B
Gemma 4 26B A4B leads, 16.7 against 6.7.
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 GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Long documents
Listed context window
Gemma 4 26B A4B
Gemma 4 26B A4B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
Gemma 4 26B A4B $0.0004, GPT-4o-mini $0.0004 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B not benchmarked, GPT-4o-mini not benchmarked.
- Widest category
- Coding, 27.9 points apart on average over 1 shared benchmark.
- Widest single gap
- IFBench: Gemma 4 26B A4B 72.4% against GPT-4o-mini 31.0%, 41.5 points apart on a 0 to 100 scale.
- Output price
- Both cost $0.60 per million output tokens.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GPT-4o-mini 128K.
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 | GPT-4o-mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 8 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| LMArena WebDev | 1360 | Not measured | Only Gemma 4 26B A4B measured |
| AA Coding Index | 39.3 | 11.4 | Gemma 4 26B A4B |
| LiveCodeBench (Vals AI) | Not measured | 26.4% | Only GPT-4o-mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 23.4% | Only GPT-4o-mini measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | Not measured | Only Gemma 4 26B A4B measured |
| WeirdML | 35.2% | Not measured | Only Gemma 4 26B A4B measured |
| ALE-Bench | 927.2 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: coding | 1446 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: software and IT | 1454 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | Not measured | Only Gemma 4 26B A4B measured |
| SciCode | Not measured | 1.5% | Only GPT-4o-mini measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 6.7 | Gemma 4 26B A4B |
| Epoch Capabilities Index | 141.9 | 126.5 | Gemma 4 26B A4B |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| τ²-Bench Telecom | 43.6% | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 44.2% | Only GPT-4o-mini measured |
| MMMU Pro (Vals AI) | Not measured | 56.6% | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 42.6% | Gemma 4 26B A4B |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 4.2% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | 73.2% | Not measured | Only Gemma 4 26B A4B measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o-mini measured |
| LMArena Text: hard prompts | 1438 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: expert | 1447 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts in English | 1448 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: diagrams | 1264 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: homework | 1293 | Not measured | Only Gemma 4 26B A4B measured |
| Kagi LLM Benchmark | Not measured | 28.8% | Only GPT-4o-mini measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| AIME | Not measured | 11.5% | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | Not measured | 72.6% | Only GPT-4o-mini measured |
| MGSM (Vals AI) | Not measured | 86.2% | Only GPT-4o-mini measured |
| AA Math Index | Not measured | 14.7 | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.7% | Only GPT-4o-mini measured |
| OTIS Mock AIME | 82.2% | Not measured | Only Gemma 4 26B A4B measured |
| GSM8K | Not measured | 91.3% | Only GPT-4o-mini measured |
| LMArena Text: math | 1470 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: mathematical work | 1475 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 62.7% | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | Not measured | 45.5% | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | Not measured | 60.5% | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | Not measured | 54.5% | Only GPT-4o-mini measured |
| MedQA (Vals AI) | Not measured | 72.4% | Only GPT-4o-mini measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 64.8% | Only GPT-4o-mini measured |
| MMLU | Not measured | 81.8% | Only GPT-4o-mini measured |
| LMArena Text: science | 1446 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: medicine and healthcare | 1428 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: legal and government | 1457 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: business and finance | 1429 | Not measured | Only Gemma 4 26B A4B measured |
| FACTS Benchmark Suite | 42.7% | Not measured | Only Gemma 4 26B A4B measured |
| 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 | GPT-4o-mini | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemma 4 26B A4B | GPT-4o-mini | Leader |
|---|---|---|---|
| IFBench | 72.4% | 31.0% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 65.7% | Not measured | Only Gemma 4 26B A4B measured |
| DTBench | 74.9% | 54.4% | Gemma 4 26B A4B |
| LMCA | 29.7% | 10.4% | Gemma 4 26B A4B |
| PIQA | Not measured | 88.7% | Only GPT-4o-mini measured |
| LMArena Text | 1434 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: instruction following | 1420 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: creative writing | 1400 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision | 1260 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1444 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: non-English | 1421 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Chinese | 1495 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: French | 1460 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Spanish | 1415 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Russian | 1434 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: multi-turn | 1441 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: longer queries | 1427 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: writing and language | 1405 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: entertainment and media | 1403 | Not measured | Only Gemma 4 26B A4B measured |
| 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 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-4o-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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 GPT-4o-mini |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 3, 2026 | July 18, 2024 |
| Context window | 262K | 128K |
| Input $/Mtok | $0.15 | $0.15 |
| Output $/Mtok | $0.60 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B better than GPT-4o-mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 4 26B A4B for a larger context window (262K against 128K tokens).
Which is cheaper, Gemma 4 26B A4B or GPT-4o-mini?
Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-4o-mini costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 26B A4B or GPT-4o-mini?
Gemma 4 26B A4B, with 262K tokens against 128K.
How many benchmarks is the Gemma 4 26B A4B vs GPT-4o-mini comparison based on?
8 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 GPT-4o-mini's on 0. Where only one model has a result, the page says so instead of naming a winner.