Gemma 4 26B A4B vs GPT-5.2
GPT-5.2 leads Gemma 4 26B A4B on the Artificial Analysis Intelligence Index, 30.4 to 16.7, and Gemma 4 26B A4B costs 23.3x less per output token ($0.60 vs $14.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.
Gemma 4 26B A4B or GPT-5.2: which to pick
Only GPT-5.2 has a coding score, 55.9 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 23.3x cheaper ($0.60 vs $14.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 51
- Gemma 4 26B A4B only
- 4
- GPT-5.2 only
- 63
- 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-5.2 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.2
GPT-5.2 leads, 30.4 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-5.2 has a GPQA Diamond result, 91.7%.
Directional only
Math
AIME
No call
Only GPT-5.2 has a AIME result, 96.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.2 has a MMLU Pro result, 86.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.2 has a Design Arena: websites result, 1195.
Directional only
Long documents
Listed context window
GPT-5.2
GPT-5.2 takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0004, GPT-5.2 $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2 has the number, $1.91.
Directional only
At a glance
- Coding index
- Gemma 4 26B A4B not benchmarked, GPT-5.2 55.9 from 3 benchmarks.
- Widest category
- Agentic work, 41.2 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against GPT-5.2 84.8%, 41.2 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.60 against GPT-5.2 $14.00 per million output tokens, 23.3x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GPT-5.2 400K.
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-5.2 | Ties |
|---|---|---|---|---|
| Coding | 2 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 4 | 4 | ||
| Math | 2 | 1 | ||
| Knowledge | 4 | 1 | ||
| General | 20 | 5 | ||
| All shared boards | 32 | 19 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index25
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 72.8% | Only GPT-5.2 measured |
| SWE-bench Multilingual | Not measured | 66.7% | Only GPT-5.2 measured |
| LMArena WebDev | 1360 | 1417 | GPT-5.2 |
| AA Coding Index | 39.3 | Not measured | Only Gemma 4 26B A4B measured |
| LiveCodeBench (Vals AI) | Not measured | 85.4% | Only GPT-5.2 measured |
| SWE-bench Verified (Vals AI) | Not measured | 75.8% | Only GPT-5.2 measured |
| Vibe Code Bench (Vals AI) | Not measured | 53.5% | Only GPT-5.2 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 89.4% | Only GPT-5.2 measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 47.0% | GPT-5.2 |
| Terminal-Bench | Not measured | 64.9% | Only GPT-5.2 measured |
| GSO-Bench | Not measured | 27.5% | Only GPT-5.2 measured |
| WeirdML | 35.2% | 72.2% | GPT-5.2 |
| ALE-Bench | 927.2 | 1293.5 | GPT-5.2 |
| LMArena Text: coding | 1446 | 1442 | Gemma 4 26B A4B |
| LMArena Text: software and IT | 1454 | 1434 | Gemma 4 26B A4B |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | 1427 | GPT-5.2 |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 30.4 | GPT-5.2 |
| Epoch Capabilities Index | 141.9 | 153.7 | GPT-5.2 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| Design Arena: agents building web apps | Not measured | 1086 | Only GPT-5.2 measured |
| Design Arena: agents building full-stack apps | Not measured | 1043 | Only GPT-5.2 measured |
| Design Arena: agents building mobile apps | Not measured | 1093 | Only GPT-5.2 measured |
| Design Arena: agents building Android apps | Not measured | 1059 | Only GPT-5.2 measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GPT-5.2 measured |
| τ²-Bench Telecom | 43.6% | 84.8% | GPT-5.2 |
| METR time horizons | Not measured | 75.3% | Only GPT-5.2 measured |
| Remote Labor Index | Not measured | 2.5% | Only GPT-5.2 measured |
| GDPval | Not measured | 49.7% | Only GPT-5.2 measured |
| DeepResearch Bench | Not measured | 41.1% | Only GPT-5.2 measured |
| Vending-Bench 2 | Not measured | $3,591 | Only GPT-5.2 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 55.9% | Only GPT-5.2 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 91.7% | Only GPT-5.2 measured |
| MMMU Pro (Vals AI) | Not measured | 86.7% | Only GPT-5.2 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 90.3% | GPT-5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 37.7% | GPT-5.2 |
| GPQA Diamond (Epoch AI run) | 73.2% | 91.4% | GPT-5.2 |
| ARC-AGI | Not measured | 86.2% | Only GPT-5.2 measured |
| ARC-AGI-2 | Not measured | 52.9% | Only GPT-5.2 measured |
| SimpleBench | Not measured | 45.8% | Only GPT-5.2 measured |
| Chess puzzles | Not measured | 48.0% | Only GPT-5.2 measured |
| Mystery game puzzles | Not measured | 23.0% | Only GPT-5.2 measured |
| EBR-bench | Not measured | 23.0% | Only GPT-5.2 measured |
| VPCT | Not measured | 84.0% | Only GPT-5.2 measured |
| LMArena Text: hard prompts | 1438 | 1428 | Gemma 4 26B A4B |
| LMArena Text: expert | 1447 | 1445 | Gemma 4 26B A4B |
| LMArena Text: hard prompts in English | 1448 | 1431 | Gemma 4 26B A4B |
| LMArena Vision: diagrams | 1264 | 1265 | GPT-5.2 |
| LMArena Vision: homework | 1293 | 1276 | Gemma 4 26B A4B |
| Kagi LLM Benchmark | Not measured | 73.3% | Only GPT-5.2 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| AIME | Not measured | 96.9% | Only GPT-5.2 measured |
| MGSM (Vals AI) | Not measured | 94.0% | Only GPT-5.2 measured |
| AA Math Index | Not measured | 99.0 | Only GPT-5.2 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 99.0% | Only GPT-5.2 measured |
| OTIS Mock AIME | 82.2% | 96.1% | GPT-5.2 |
| FrontierMath, tiers 1 to 3 | Not measured | 67.4% | Only GPT-5.2 measured |
| FrontierMath, tier 4 | Not measured | 31.7% | Only GPT-5.2 measured |
| ProofBench | Not measured | 15.0% | Only GPT-5.2 measured |
| LMArena Text: math | 1470 | 1440 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1475 | 1442 | Gemma 4 26B A4B |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.2% | Only GPT-5.2 measured |
| LegalBench (Vals AI) | Not measured | 82.8% | Only GPT-5.2 measured |
| CaseLaw (Vals AI) | Not measured | 66.0% | Only GPT-5.2 measured |
| CorpFin (Vals AI) | Not measured | 65.9% | Only GPT-5.2 measured |
| TaxEval (Vals AI) | Not measured | 75.8% | Only GPT-5.2 measured |
| MortgageTax (Vals AI) | Not measured | 67.1% | Only GPT-5.2 measured |
| MedQA (Vals AI) | Not measured | 94.1% | Only GPT-5.2 measured |
| MedCode (Vals AI) | Not measured | 49.8% | Only GPT-5.2 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.4% | Only GPT-5.2 measured |
| SimpleQA Verified | Not measured | 37.1% | Only GPT-5.2 measured |
| LMArena Text: science | 1446 | 1425 | Gemma 4 26B A4B |
| LMArena Text: medicine and healthcare | 1428 | 1425 | Gemma 4 26B A4B |
| LMArena Text: legal and government | 1457 | 1427 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1429 | 1414 | Gemma 4 26B A4B |
| FACTS Benchmark Suite | 42.7% | 48.5% | GPT-5.2 |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1195 | Only GPT-5.2 measured |
| Design Arena: UI components | Not measured | 1190 | Only GPT-5.2 measured |
| Design Arena: game dev | Not measured | 1195 | Only GPT-5.2 measured |
| Design Arena: data viz | Not measured | 1202 | Only GPT-5.2 measured |
| Design Arena: 3D | Not measured | 1079 | Only GPT-5.2 measured |
| Design Arena: all code categories | Not measured | 1170 | Only GPT-5.2 measured |
| Design Arena: SVG | Not measured | 1139 | Only GPT-5.2 measured |
| Design Arena: ASCII art | Not measured | 1152 | Only GPT-5.2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index205
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 49.3% | Only GPT-5.2 measured |
| MedScribe (Vals AI) | Not measured | 84.4% | Only GPT-5.2 measured |
| IFBench | 72.4% | 75.4% | GPT-5.2 |
| Long context reasoning (AA-LCR) | 65.7% | 82.7% | GPT-5.2 |
| DTBench | 74.9% | 90.9% | GPT-5.2 |
| LMCA | 29.7% | 43.9% | GPT-5.2 |
| CL-bench | Not measured | 18.2% | Only GPT-5.2 measured |
| Furniture assembly | Not measured | 38.3% | Only GPT-5.2 measured |
| LMArena Text | 1434 | 1416 | Gemma 4 26B A4B |
| LMArena Text: instruction following | 1420 | 1409 | Gemma 4 26B A4B |
| LMArena Text: creative writing | 1400 | 1376 | Gemma 4 26B A4B |
| LMArena Vision | 1260 | 1246 | Gemma 4 26B A4B |
| LMArena Text: English | 1444 | 1422 | Gemma 4 26B A4B |
| LMArena Text: non-English | 1421 | 1405 | Gemma 4 26B A4B |
| LMArena Text: Chinese | 1495 | 1447 | Gemma 4 26B A4B |
| LMArena Text: German | Not measured | 1444 | Only GPT-5.2 measured |
| LMArena Text: Japanese | Not measured | 1420 | Only GPT-5.2 measured |
| LMArena Text: Korean | Not measured | 1374 | Only GPT-5.2 measured |
| LMArena Text: French | 1460 | 1454 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1415 | 1413 | Gemma 4 26B A4B |
| LMArena Text: Russian | 1434 | 1415 | Gemma 4 26B A4B |
| LMArena Text: Polish | Not measured | 1426 | Only GPT-5.2 measured |
| LMArena Text: multi-turn | 1441 | 1419 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1427 | 1413 | Gemma 4 26B A4B |
| LMArena Text: writing and language | 1405 | 1392 | Gemma 4 26B A4B |
| LMArena Text: entertainment and media | 1403 | 1378 | Gemma 4 26B A4B |
| LMArena Vision: English | 1256 | 1243 | Gemma 4 26B A4B |
| LMArena Vision: Chinese | 1312 | 1305 | Gemma 4 26B A4B |
| LMArena Vision: reading text | 1268 | 1257 | Gemma 4 26B A4B |
| LMArena Vision: humor | 1272 | 1227 | Gemma 4 26B A4B |
| LMArena Vision: captioning | 1297 | 1267 | Gemma 4 26B A4B |
| LMArena Vision: recognizing things | 1191 | 1232 | GPT-5.2 |
| LMArena Vision: creative writing | 1256 | 1225 | Gemma 4 26B A4B |
| LMArena Document | Not measured | 1405 | Only GPT-5.2 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GPT-5.2 | 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-5.2 |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 3, 2026 | December 10, 2025 |
| Context window | 262K | 400K |
| Input $/Mtok | $0.15 | $1.75 |
| Output $/Mtok | $0.60 | $14.00 |
| Coding index | Not benchmarked | 55.9 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | Not computable | $1.91 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B better than GPT-5.2 for coding?
Only GPT-5.2 has a coding score, 55.9 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 23.3x cheaper ($0.60 vs $14.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Gemma 4 26B A4B or GPT-5.2?
Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Cost per solved task is known for GPT-5.2 only.
Which has the bigger context window, Gemma 4 26B A4B or GPT-5.2?
GPT-5.2, with 400K tokens against 262K.
How many benchmarks is the Gemma 4 26B A4B vs GPT-5.2 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-5.2's on 3. Where only one model has a result, the page says so instead of naming a winner.