Gemma 4 26B A4B vs GLM 4.6
Updated October 21, 2026. 35 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 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B.
Pick Gemma 4 26B A4B when output tokens cost 8.6x less, or when the context window is larger, 262K against 205K tokens.
- Shared results
- 35
- Gemma 4 26B A4B only
- 19
- GLM 4.6 only
- 31
- 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 4.6
GLM 4.6 scores 52.2 against 22.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 4.6
GLM 4.6 leads, 18.5 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
Reasoning
GPQA Diamond
No call
Only GLM 4.6 has a GPQA Diamond result, 74.5%.
Directional only
Math
AIME
No call
Only GLM 4.6 has a AIME result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 4.6 has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
No call
Only GLM 4.6 has a Design Arena: websites result, 1174.
Directional only
Long documents
Listed context window
Gemma 4 26B A4B
Gemma 4 26B A4B takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0002, GLM 4.6 $0.0016 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B 22.8 from 1 benchmark, GLM 4.6 52.2 from 2 benchmarks.
- Widest category
- Agentic work, 33.3 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against GLM 4.6 76.9%, 33.3 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.255 against GLM 4.6 $2.20 per million output tokens, 8.6x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GLM 4.6 205K.
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 4.6 | Ties |
|---|---|---|---|---|
| Coding | 3 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 4 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 2 | ||
| General | 7 | 8 | ||
| All shared boards | 18 | 17 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index34
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 68.2% | Only GLM 4.6 measured |
| LMArena WebDev | 1360 | 1341 | Gemma 4 26B A4B |
| AA Coding Index | 39.3 | 45.8 | GLM 4.6 |
| LiveCodeBench (Vals AI) | Not measured | 81.0% | Only GLM 4.6 measured |
| Vibe Code Bench (Vals AI) | Not measured | 3.1% | Only GLM 4.6 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 69.5% | Only GLM 4.6 measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 28.8% | GLM 4.6 |
| Terminal-Bench | Not measured | 24.5% | Only GLM 4.6 measured |
| WeirdML | 35.2% | Not measured | Only Gemma 4 26B A4B measured |
| ALE-Bench | 927.2 | 340.8 | Gemma 4 26B A4B |
| LMArena Text: coding | 1446 | 1449 | GLM 4.6 |
| LMArena Text: software and IT | 1454 | 1455 | GLM 4.6 |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | 1350 | Gemma 4 26B A4B |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 18.5 | GLM 4.6 |
| 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 4.6 | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| Design Arena: agents building full-stack apps | Not measured | 1029 | Only GLM 4.6 measured |
| Design Arena: agents building mobile apps | Not measured | 1096 | Only GLM 4.6 measured |
| Design Arena: agents building Android apps | Not measured | 1090 | Only GLM 4.6 measured |
| Design Arena: agents building Godot games | Not measured | 1180 | Only GLM 4.6 measured |
| τ²-Bench Telecom | 43.6% | 76.9% | GLM 4.6 |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 74.5% | Only GLM 4.6 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 78.0% | Gemma 4 26B A4B |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 14.5% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | 73.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts | 1438 | 1440 | GLM 4.6 |
| LMArena Text: expert | 1447 | 1432 | Gemma 4 26B A4B |
| LMArena Text: hard prompts in English | 1448 | 1445 | 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 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| AIME | Not measured | 92.7% | Only GLM 4.6 measured |
| MGSM (Vals AI) | Not measured | 89.8% | Only GLM 4.6 measured |
| AA Math Index | Not measured | 86.0 | Only GLM 4.6 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 86.0% | Only GLM 4.6 measured |
| OTIS Mock AIME | 82.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: math | 1470 | 1432 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1475 | 1447 | Gemma 4 26B A4B |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.2% | Only GLM 4.6 measured |
| LegalBench (Vals AI) | Not measured | 79.6% | Only GLM 4.6 measured |
| CorpFin (Vals AI) | Not measured | 56.8% | Only GLM 4.6 measured |
| TaxEval (Vals AI) | Not measured | 66.2% | Only GLM 4.6 measured |
| MedQA (Vals AI) | Not measured | 92.2% | Only GLM 4.6 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 82.9% | Only GLM 4.6 measured |
| LMArena Text: science | 1446 | 1456 | GLM 4.6 |
| LMArena Text: medicine and healthcare | 1428 | 1455 | GLM 4.6 |
| LMArena Text: legal and government | 1457 | 1448 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1429 | 1416 | Gemma 4 26B A4B |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1174 | Only GLM 4.6 measured |
| Design Arena: UI components | Not measured | 1147 | Only GLM 4.6 measured |
| Design Arena: game dev | Not measured | 1151 | Only GLM 4.6 measured |
| Design Arena: data viz | Not measured | 1161 | Only GLM 4.6 measured |
| Design Arena: 3D | Not measured | 1129 | Only GLM 4.6 measured |
| Design Arena: all code categories | Not measured | 1166 | Only GLM 4.6 measured |
| Design Arena: SVG | Not measured | 1108 | Only GLM 4.6 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index78
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | Leader |
|---|---|---|---|
| IFBench | 72.4% | 43.4% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 65.7% | 54.0% | Gemma 4 26B A4B |
| 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 | 1440 | GLM 4.6 |
| LMArena Text: instruction following | 1420 | 1410 | Gemma 4 26B A4B |
| LMArena Text: creative writing | 1400 | 1412 | GLM 4.6 |
| LMArena Vision | 1260 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1444 | 1449 | GLM 4.6 |
| LMArena Text: non-English | 1421 | 1426 | GLM 4.6 |
| LMArena Text: Chinese | 1495 | 1499 | GLM 4.6 |
| LMArena Text: German | Not measured | 1447 | Only GLM 4.6 measured |
| LMArena Text: Japanese | Not measured | 1393 | Only GLM 4.6 measured |
| LMArena Text: Korean | Not measured | 1400 | Only GLM 4.6 measured |
| LMArena Text: French | 1460 | 1459 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1415 | 1436 | GLM 4.6 |
| LMArena Text: Russian | 1434 | 1418 | Gemma 4 26B A4B |
| LMArena Text: Polish | Not measured | 1447 | Only GLM 4.6 measured |
| LMArena Text: multi-turn | 1441 | 1427 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1427 | 1422 | Gemma 4 26B A4B |
| LMArena Text: writing and language | 1405 | 1415 | GLM 4.6 |
| LMArena Text: entertainment and media | 1403 | 1409 | GLM 4.6 |
| 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 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GLM 4.6 | 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 4.6 |
|---|---|---|
| Maker | Z.ai | |
| Weights | Open weights | Open weights |
| Released | April 3, 2026 | September 30, 2025 |
| Context window | 262K | 205K |
| Input $/Mtok | $0.0765 | $0.55 |
| Output $/Mtok | $0.255 | $2.20 |
| Coding index | 22.8 | 52.2 |
| 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 GLM 4.6 for coding?
Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 22.8 for Gemma 4 26B A4B. Pick Gemma 4 26B A4B when output tokens cost 8.6x less, or when the context window is larger, 262K against 205K tokens.
Which is cheaper, Gemma 4 26B A4B or GLM 4.6?
Gemma 4 26B A4B costs $0.0765 per million input tokens and $0.255 per million output tokens; GLM 4.6 costs $0.55 and $2.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 26B A4B or GLM 4.6?
Gemma 4 26B A4B, with 262K tokens against 205K.
How many benchmarks is the Gemma 4 26B A4B vs GLM 4.6 comparison based on?
35 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 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.