Gemma 4 26B A4B vs GLM 5V Turbo
Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 5V Turbo for coding: it scores 28.8 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B.
Pick Gemma 4 26B A4B when output tokens cost 15.7x less, or when the context window is larger, 262K against 203K tokens.
- Shared results
- 44
- Gemma 4 26B A4B only
- 10
- GLM 5V Turbo only
- 21
- 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
GLM 5V Turbo
GLM 5V Turbo scores 28.8 against 22.8.
One benchmark behind each score
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 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
Web design
Design Arena: websites
No call
Only GLM 5V Turbo has a Design Arena: websites result, 1230.
Directional only
Long documents
Listed context window
Gemma 4 26B A4B
Gemma 4 26B A4B takes 262K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0002, GLM 5V Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B 22.8 from 1 benchmark, GLM 5V Turbo 28.8 from 1 benchmark.
- Widest category
- Agentic work, 55.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against GLM 5V Turbo 98.5%, 55.0 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.255 against GLM 5V Turbo $4.00 per million output tokens, 15.7x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GLM 5V Turbo 203K.
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 | GLM 5V Turbo | Ties |
|---|---|---|---|---|
| Coding | 1 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 5 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 3 | ||
| General | 9 | 14 | ||
| All shared boards | 15 | 29 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index15
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| LMArena WebDev | 1360 | 1402 | GLM 5V Turbo |
| AA Coding Index | 39.3 | Not measured | Only Gemma 4 26B A4B measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 32.6% | GLM 5V Turbo |
| 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 | 1466 | GLM 5V Turbo |
| LMArena Text: software and IT | 1454 | 1460 | GLM 5V Turbo |
| LMArena WebDev: React | 1351 | 1386 | GLM 5V Turbo |
| LMArena WebDev: HTML | 1362 | 1356 | Gemma 4 26B A4B |
| LMArena WebDev: from an image | Not measured | 1425 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 23.5 | GLM 5V Turbo |
| Epoch Capabilities Index | 141.9 | Not measured | Only Gemma 4 26B A4B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| Design Arena: agents building web apps | Not measured | 1124 | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | Not measured | 1149 | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | Not measured | 1134 | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | Not measured | 1267 | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | Not measured | 957 | Only GLM 5V Turbo measured |
| Design Arena: agents building games | Not measured | 1102 | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | Not measured | 1120 | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | Not measured | 1152 | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 43.6% | 98.5% | GLM 5V Turbo |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.2% | 80.9% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 17.1% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | 73.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts | 1438 | 1443 | GLM 5V Turbo |
| LMArena Text: expert | 1447 | 1453 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1448 | 1456 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1264 | 1286 | GLM 5V Turbo |
| LMArena Vision: homework | 1293 | 1273 | Gemma 4 26B A4B |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| OTIS Mock AIME | 82.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: math | 1470 | 1442 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1475 | 1447 | Gemma 4 26B A4B |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| LMArena Text: science | 1446 | 1448 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1428 | 1433 | GLM 5V Turbo |
| LMArena Text: legal and government | 1457 | 1436 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1429 | 1435 | GLM 5V Turbo |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1230 | Only GLM 5V Turbo measured |
| Design Arena: UI components | Not measured | 1213 | Only GLM 5V Turbo measured |
| Design Arena: game dev | Not measured | 1219 | Only GLM 5V Turbo measured |
| Design Arena: data viz | Not measured | 1202 | Only GLM 5V Turbo measured |
| Design Arena: 3D | Not measured | 1209 | Only GLM 5V Turbo measured |
| Design Arena: all code categories | Not measured | 1228 | Only GLM 5V Turbo measured |
| Design Arena: SVG | Not measured | 1151 | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | Not measured | 1118 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index914
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | Leader |
|---|---|---|---|
| IFBench | 72.4% | 61.1% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 65.7% | 70.3% | GLM 5V Turbo |
| DTBench | 74.9% | Not measured | Only Gemma 4 26B A4B measured |
| LMCA | 29.7% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text | 1434 | 1437 | GLM 5V Turbo |
| LMArena Text: instruction following | 1420 | 1423 | GLM 5V Turbo |
| LMArena Text: creative writing | 1400 | 1417 | GLM 5V Turbo |
| LMArena Vision | 1260 | 1264 | GLM 5V Turbo |
| LMArena Text: English | 1444 | 1454 | GLM 5V Turbo |
| LMArena Text: non-English | 1421 | 1420 | Gemma 4 26B A4B |
| LMArena Text: Chinese | 1495 | 1491 | Gemma 4 26B A4B |
| LMArena Text: German | Not measured | 1422 | Only GLM 5V Turbo measured |
| LMArena Text: Korean | Not measured | 1397 | Only GLM 5V Turbo measured |
| LMArena Text: French | 1460 | 1443 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1415 | 1452 | GLM 5V Turbo |
| LMArena Text: Russian | 1434 | 1432 | Gemma 4 26B A4B |
| LMArena Text: Polish | Not measured | 1432 | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1441 | 1431 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1427 | 1438 | GLM 5V Turbo |
| LMArena Text: writing and language | 1405 | 1420 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1403 | 1407 | GLM 5V Turbo |
| LMArena Vision: English | 1256 | 1274 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1312 | 1329 | GLM 5V Turbo |
| LMArena Vision: reading text | 1268 | 1270 | GLM 5V Turbo |
| LMArena Vision: humor | 1272 | 1268 | Gemma 4 26B A4B |
| LMArena Vision: captioning | 1297 | 1264 | Gemma 4 26B A4B |
| LMArena Vision: recognizing things | 1191 | 1241 | GLM 5V Turbo |
| LMArena Vision: creative writing | 1256 | 1252 | Gemma 4 26B A4B |
| LMArena Document | Not measured | 1416 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GLM 5V Turbo | 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 | Z.ai GLM 5V Turbo |
|---|---|---|
| Maker | Z.ai | |
| Weights | Open weights | No public weights listed |
| Released | April 3, 2026 | April 1, 2026 |
| Context window | 262K | 203K |
| Input $/Mtok | $0.0765 | $1.20 |
| Output $/Mtok | $0.255 | $4.00 |
| Coding index | 22.8 | 28.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B better than GLM 5V Turbo for coding?
Pick GLM 5V Turbo for coding: it scores 28.8 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B. Pick Gemma 4 26B A4B when output tokens cost 15.7x less, or when the context window is larger, 262K against 203K tokens.
Which is cheaper, Gemma 4 26B A4B or GLM 5V Turbo?
Gemma 4 26B A4B costs $0.0765 per million input tokens and $0.255 per million output tokens; GLM 5V Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 26B A4B or GLM 5V Turbo?
Gemma 4 26B A4B, with 262K tokens against 203K.
How many benchmarks is the Gemma 4 26B A4B vs GLM 5V Turbo comparison based on?
44 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 GLM 5V Turbo's on 1. Where only one model has a result, the page says so instead of naming a winner.