Gemma 4 26B A4B vs GPT-5.4
GPT-5.4 leads Gemma 4 26B A4B on the Artificial Analysis Intelligence Index, 39.0 to 16.7, and Gemma 4 26B A4B costs 25.0x less per output token ($0.60 vs $15.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.
Gemma 4 26B A4B or GPT-5.4: which to pick
Only GPT-5.4 has a coding score, 64.4 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 25.0x cheaper ($0.60 vs $15.00 per million).
- Shared results
- 51
- Gemma 4 26B A4B only
- 4
- GPT-5.4 only
- 59
- 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
Only GPT-5.4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.4
GPT-5.4 leads, 39.0 against 16.7.
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-5.4 has a GPQA Diamond result, 91.7%.
Directional only
Math
AIME
No call
Only GPT-5.4 has a AIME result, 96.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 has a MMLU Pro result, 87.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.4 has a Design Arena: websites result, 1198.
Directional only
Long documents
Listed context window
GPT-5.4
GPT-5.4 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0004, GPT-5.4 $0.010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 has the number, $1.02.
Directional only
At a glance
- Coding index
- Gemma 4 26B A4B not benchmarked, GPT-5.4 64.4 from 3 benchmarks.
- Widest category
- Agentic work, 43.6 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against GPT-5.4 87.1%, 43.6 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.60 against GPT-5.4 $15.00 per million output tokens, 25.0x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GPT-5.4 1.05M.
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-5.4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 9 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 8 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 24 | ||
| All shared boards | 0 | 51 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index09
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1360 | 1464 | GPT-5.4 |
| AA Coding Index | 39.3 | 71.1 | GPT-5.4 |
| LiveCodeBench (Vals AI) | Not measured | 84.1% | Only GPT-5.4 measured |
| SWE-bench Verified (Vals AI) | Not measured | 78.2% | Only GPT-5.4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 67.4% | Only GPT-5.4 measured |
| Code migration (Vals AI) | Not measured | 35.0% | Only GPT-5.4 measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only GPT-5.4 measured |
| SkillsBench (Vals AI) | Not measured | 51.7% | Only GPT-5.4 measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 57.6% | GPT-5.4 |
| Terminal-Bench | Not measured | 81.8% | Only GPT-5.4 measured |
| GSO-Bench | Not measured | 31.4% | Only GPT-5.4 measured |
| WeirdML | 35.2% | 77.7% | GPT-5.4 |
| MirrorCode | Not measured | 15.6% | Only GPT-5.4 measured |
| ALE-Bench | 927.2 | 1607.0 | GPT-5.4 |
| LMArena Text: coding | 1446 | 1496 | GPT-5.4 |
| LMArena Text: software and IT | 1454 | 1491 | GPT-5.4 |
| LMArena WebDev: React | 1351 | 1454 | GPT-5.4 |
| LMArena WebDev: HTML | 1362 | 1478 | GPT-5.4 |
| LMArena WebDev: from an image | Not measured | 1436 | Only GPT-5.4 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 39.0 | GPT-5.4 |
| Epoch Capabilities Index | 141.9 | 157.3 | GPT-5.4 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| Design Arena: agents building web apps | Not measured | 1059 | Only GPT-5.4 measured |
| Design Arena: agents building full-stack apps | Not measured | 1017 | Only GPT-5.4 measured |
| Design Arena: agents building mobile apps | Not measured | 1087 | Only GPT-5.4 measured |
| Design Arena: agents building Android apps | Not measured | 1031 | Only GPT-5.4 measured |
| Design Arena: agents building Godot games | Not measured | 1135 | Only GPT-5.4 measured |
| τ²-Bench Telecom | 43.6% | 87.1% | GPT-5.4 |
| APEX-Agents | Not measured | 52.4% | Only GPT-5.4 measured |
| METR time horizons | Not measured | 74.3% | Only GPT-5.4 measured |
| DeepResearch Bench | Not measured | 35.1% | Only GPT-5.4 measured |
| PostTrainBench | Not measured | 19.0% | Only GPT-5.4 measured |
| Vending-Bench 2 | Not measured | $6,144 | Only GPT-5.4 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 91.7% | Only GPT-5.4 measured |
| MMMU Pro (Vals AI) | Not measured | 87.5% | Only GPT-5.4 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 92.0% | GPT-5.4 |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 43.7% | GPT-5.4 |
| GPQA Diamond (Epoch AI run) | 73.2% | 93.3% | GPT-5.4 |
| ARC-AGI | Not measured | 93.7% | Only GPT-5.4 measured |
| ARC-AGI-2 | Not measured | 74.0% | Only GPT-5.4 measured |
| Chess puzzles | Not measured | 48.0% | Only GPT-5.4 measured |
| Mystery game puzzles | Not measured | 37.0% | Only GPT-5.4 measured |
| EBR-bench | Not measured | 25.4% | Only GPT-5.4 measured |
| LMArena Text: hard prompts | 1438 | 1485 | GPT-5.4 |
| LMArena Text: expert | 1447 | 1507 | GPT-5.4 |
| LMArena Text: hard prompts in English | 1448 | 1479 | GPT-5.4 |
| LMArena Vision: diagrams | 1264 | 1327 | GPT-5.4 |
| LMArena Vision: homework | 1293 | 1336 | GPT-5.4 |
| Kagi LLM Benchmark | Not measured | 63.8% | Only GPT-5.4 measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| AIME | Not measured | 96.7% | Only GPT-5.4 measured |
| OTIS Mock AIME | 82.2% | 97.8% | GPT-5.4 |
| FrontierMath, tiers 1 to 3 | Not measured | 78.6% | Only GPT-5.4 measured |
| FrontierMath, tier 4 | Not measured | 49.0% | Only GPT-5.4 measured |
| ProofBench | Not measured | 56.0% | Only GPT-5.4 measured |
| LMArena Text: math | 1470 | 1488 | GPT-5.4 |
| LMArena Text: mathematical work | 1475 | 1497 | GPT-5.4 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.5% | Only GPT-5.4 measured |
| LegalBench (Vals AI) | Not measured | 86.0% | Only GPT-5.4 measured |
| CaseLaw (Vals AI) | Not measured | 63.8% | Only GPT-5.4 measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only GPT-5.4 measured |
| TaxEval (Vals AI) | Not measured | 74.0% | Only GPT-5.4 measured |
| MortgageTax (Vals AI) | Not measured | 68.3% | Only GPT-5.4 measured |
| MedQA (Vals AI) | Not measured | 96.1% | Only GPT-5.4 measured |
| MedCode (Vals AI) | Not measured | 41.3% | Only GPT-5.4 measured |
| SimpleQA Verified | Not measured | 45.1% | Only GPT-5.4 measured |
| LMArena Text: science | 1446 | 1479 | GPT-5.4 |
| LMArena Text: medicine and healthcare | 1428 | 1458 | GPT-5.4 |
| LMArena Text: legal and government | 1457 | 1486 | GPT-5.4 |
| LMArena Text: business and finance | 1429 | 1474 | GPT-5.4 |
| FACTS Benchmark Suite | 42.7% | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1198 | Only GPT-5.4 measured |
| Design Arena: UI components | Not measured | 1212 | Only GPT-5.4 measured |
| Design Arena: game dev | Not measured | 1194 | Only GPT-5.4 measured |
| Design Arena: data viz | Not measured | 1196 | Only GPT-5.4 measured |
| Design Arena: 3D | Not measured | 1065 | Only GPT-5.4 measured |
| Design Arena: all code categories | Not measured | 1179 | Only GPT-5.4 measured |
| Design Arena: SVG | Not measured | 1141 | Only GPT-5.4 measured |
| Design Arena: ASCII art | Not measured | 1188 | Only GPT-5.4 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index024
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 43.3% | Only GPT-5.4 measured |
| MedScribe (Vals AI) | Not measured | 77.5% | Only GPT-5.4 measured |
| IFBench | 72.4% | 73.9% | GPT-5.4 |
| Long context reasoning (AA-LCR) | 65.7% | 82.0% | GPT-5.4 |
| DTBench | 74.9% | 94.4% | GPT-5.4 |
| LMCA | 29.7% | 52.0% | GPT-5.4 |
| CL-bench | Not measured | 27.9% | Only GPT-5.4 measured |
| Furniture assembly | Not measured | 37.5% | Only GPT-5.4 measured |
| CL-bench Life | Not measured | 21.7% | Only GPT-5.4 measured |
| LMArena Text | 1434 | 1469 | GPT-5.4 |
| LMArena Text: instruction following | 1420 | 1469 | GPT-5.4 |
| LMArena Text: creative writing | 1400 | 1439 | GPT-5.4 |
| LMArena Vision | 1260 | 1303 | GPT-5.4 |
| LMArena Text: English | 1444 | 1467 | GPT-5.4 |
| LMArena Text: non-English | 1421 | 1465 | GPT-5.4 |
| LMArena Text: Chinese | 1495 | 1520 | GPT-5.4 |
| LMArena Text: German | Not measured | 1472 | Only GPT-5.4 measured |
| LMArena Text: Japanese | Not measured | 1485 | Only GPT-5.4 measured |
| LMArena Text: Korean | Not measured | 1449 | Only GPT-5.4 measured |
| LMArena Text: French | 1460 | 1493 | GPT-5.4 |
| LMArena Text: Spanish | 1415 | 1452 | GPT-5.4 |
| LMArena Text: Russian | 1434 | 1480 | GPT-5.4 |
| LMArena Text: Polish | Not measured | 1472 | Only GPT-5.4 measured |
| LMArena Text: multi-turn | 1441 | 1482 | GPT-5.4 |
| LMArena Text: longer queries | 1427 | 1473 | GPT-5.4 |
| LMArena Text: writing and language | 1405 | 1458 | GPT-5.4 |
| LMArena Text: entertainment and media | 1403 | 1438 | GPT-5.4 |
| LMArena Vision: English | 1256 | 1301 | GPT-5.4 |
| LMArena Vision: Chinese | 1312 | 1354 | GPT-5.4 |
| LMArena Vision: reading text | 1268 | 1312 | GPT-5.4 |
| LMArena Vision: humor | 1272 | 1284 | GPT-5.4 |
| LMArena Vision: captioning | 1297 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: recognizing things | 1191 | 1251 | GPT-5.4 |
| LMArena Vision: creative writing | 1256 | 1283 | GPT-5.4 |
| LMArena Document | Not measured | 1471 | Only GPT-5.4 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-5.4 | 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 GPT-5.4 |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 3, 2026 | March 5, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.15 | $2.50 |
| Output $/Mtok | $0.60 | $15.00 |
| Coding index | Not benchmarked | 64.4 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | Not computable | $1.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B better than GPT-5.4 for coding?
Only GPT-5.4 has a coding score, 64.4 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 25.0x cheaper ($0.60 vs $15.00 per million).
Which is cheaper, Gemma 4 26B A4B or GPT-5.4?
Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.4 costs $2.50 and $15.00. Cost per solved task is known for GPT-5.4 only.
Which has the bigger context window, Gemma 4 26B A4B or GPT-5.4?
GPT-5.4, with 1.05M tokens against 262K.
How many benchmarks is the Gemma 4 26B A4B vs GPT-5.4 comparison based on?
51 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-5.4's on 3. Where only one model has a result, the page says so instead of naming a winner.