Gemma 4 26B A4B vs GLM 4.5
Gemma 4 26B A4B leads GLM 4.5 on the Artificial Analysis Intelligence Index, 16.7 to 12.8, and Gemma 4 26B A4B costs 3.7x less per output token ($0.60 vs $2.20 per million). Updated October 22, 2026; 33 benchmarks have a result for both.
Gemma 4 26B A4B or GLM 4.5: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 4 26B A4B for output tokens 3.7x cheaper ($0.60 vs $2.20 per million) and a larger context window (262K against 131K tokens).
- Shared results
- 33
- Gemma 4 26B A4B only
- 22
- GLM 4.5 only
- 28
- 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
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 12.8.
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 4.5 has a GPQA Diamond result, 72.2%.
Directional only
Math
AIME
No call
Only GLM 4.5 has a AIME result, 86.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 4.5 has a MMLU Pro result, 81.2%.
Directional only
Web design
Design Arena: websites
No call
Only GLM 4.5 has a Design Arena: websites result, 1169.
Directional only
Long documents
Listed context window
Gemma 4 26B A4B
Gemma 4 26B A4B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Gemma 4 26B A4B $0.0004, GLM 4.5 $0.0017 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B not benchmarked, GLM 4.5 not benchmarked.
- Widest category
- Math, 7.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- IFBench: Gemma 4 26B A4B 72.4% against GLM 4.5 44.1%, 28.4 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.60 against GLM 4.5 $2.20 per million output tokens, 3.7x apart.
- Context window
- Gemma 4 26B A4B takes 262K tokens, GLM 4.5 131K.
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 4.5 | Ties |
|---|---|---|---|---|
| Coding | 4 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 3 | 1 | ||
| General | 13 | 2 | ||
| All shared boards | 29 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index41
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 64.2% | Only GLM 4.5 measured |
| LMArena WebDev | 1360 | Not measured | Only Gemma 4 26B A4B measured |
| AA Coding Index | 39.3 | Not measured | Only Gemma 4 26B A4B measured |
| LiveCodeBench (Vals AI) | Not measured | 67.5% | Only GLM 4.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 73.8% | Only GLM 4.5 measured |
| SciCode | 40.0% | Not measured | Only Gemma 4 26B A4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 22.0% | Gemma 4 26B A4B |
| WeirdML | 35.2% | 40.6% | GLM 4.5 |
| ALE-Bench | 927.2 | 344.8 | Gemma 4 26B A4B |
| LMArena Text: coding | 1446 | 1434 | Gemma 4 26B A4B |
| LMArena Text: software and IT | 1454 | 1440 | Gemma 4 26B A4B |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 12.8 | Gemma 4 26B A4B |
| 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 index10
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B measured |
| τ²-Bench Telecom | 43.6% | 43.0% | Gemma 4 26B A4B |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 72.2% | Only GLM 4.5 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 78.2% | Gemma 4 26B A4B |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 13.0% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | 73.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts | 1438 | 1429 | Gemma 4 26B A4B |
| LMArena Text: expert | 1447 | 1433 | Gemma 4 26B A4B |
| LMArena Text: hard prompts in English | 1448 | 1429 | 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 |
| Kagi LLM Benchmark | Not measured | 57.9% | Only GLM 4.5 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 4.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.7% | Only GLM 4.5 measured |
| MATH 500 (Vals AI) | Not measured | 94.0% | Only GLM 4.5 measured |
| MGSM (Vals AI) | Not measured | 90.8% | Only GLM 4.5 measured |
| AA Math Index | Not measured | 73.7 | Only GLM 4.5 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.7% | Only GLM 4.5 measured |
| OTIS Mock AIME | 82.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: math | 1470 | 1427 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1475 | 1430 | Gemma 4 26B A4B |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 81.2% | Only GLM 4.5 measured |
| LegalBench (Vals AI) | Not measured | 75.6% | Only GLM 4.5 measured |
| CorpFin (Vals AI) | Not measured | 61.0% | Only GLM 4.5 measured |
| TaxEval (Vals AI) | Not measured | 72.4% | Only GLM 4.5 measured |
| MedQA (Vals AI) | Not measured | 90.0% | Only GLM 4.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.5% | Only GLM 4.5 measured |
| LMArena Text: science | 1446 | 1444 | Gemma 4 26B A4B |
| LMArena Text: medicine and healthcare | 1428 | 1455 | GLM 4.5 |
| LMArena Text: legal and government | 1457 | 1438 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1429 | 1420 | Gemma 4 26B A4B |
| FACTS Benchmark Suite | 42.7% | Not measured | Only Gemma 4 26B A4B measured |
| 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 4.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1169 | Only GLM 4.5 measured |
| Design Arena: UI components | Not measured | 1141 | Only GLM 4.5 measured |
| Design Arena: game dev | Not measured | 1144 | Only GLM 4.5 measured |
| Design Arena: data viz | Not measured | 1159 | Only GLM 4.5 measured |
| Design Arena: 3D | Not measured | 1170 | Only GLM 4.5 measured |
| Design Arena: all code categories | Not measured | 1165 | Only GLM 4.5 measured |
| Design Arena: SVG | Not measured | 1096 | Only GLM 4.5 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index132
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | Leader |
|---|---|---|---|
| IFBench | 72.4% | 44.1% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 65.7% | 52.7% | 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 |
| Creative writing (Lech Mazur) | Not measured | 73.4% | Only GLM 4.5 measured |
| LMArena Text | 1434 | 1430 | Gemma 4 26B A4B |
| LMArena Text: instruction following | 1420 | 1404 | Gemma 4 26B A4B |
| LMArena Text: creative writing | 1400 | 1395 | Gemma 4 26B A4B |
| LMArena Vision | 1260 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1444 | 1437 | Gemma 4 26B A4B |
| LMArena Text: non-English | 1421 | 1417 | Gemma 4 26B A4B |
| LMArena Text: Chinese | 1495 | 1465 | Gemma 4 26B A4B |
| LMArena Text: German | Not measured | 1407 | Only GLM 4.5 measured |
| LMArena Text: Japanese | Not measured | 1415 | Only GLM 4.5 measured |
| LMArena Text: Korean | Not measured | 1380 | Only GLM 4.5 measured |
| LMArena Text: French | 1460 | 1418 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1415 | 1454 | GLM 4.5 |
| LMArena Text: Russian | 1434 | 1413 | Gemma 4 26B A4B |
| LMArena Text: Polish | Not measured | 1422 | Only GLM 4.5 measured |
| LMArena Text: multi-turn | 1441 | 1415 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1427 | 1412 | Gemma 4 26B A4B |
| LMArena Text: writing and language | 1405 | 1403 | Gemma 4 26B A4B |
| LMArena Text: entertainment and media | 1403 | 1404 | GLM 4.5 |
| 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 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 26B A4B | GLM 4.5 | 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 4.5 |
|---|---|---|
| Maker | Z.ai | |
| Weights | Open weights | Open weights |
| Released | April 3, 2026 | July 25, 2025 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.15 | $0.60 |
| Output $/Mtok | $0.60 | $2.20 |
| 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 GLM 4.5 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 4 26B A4B for output tokens 3.7x cheaper ($0.60 vs $2.20 per million) and a larger context window (262K against 131K tokens).
Which is cheaper, Gemma 4 26B A4B or GLM 4.5?
Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 per million output tokens; GLM 4.5 costs $0.60 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 4.5?
Gemma 4 26B A4B, with 262K tokens against 131K.
How many benchmarks is the Gemma 4 26B A4B vs GLM 4.5 comparison based on?
33 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 GLM 4.5's on 0. Where only one model has a result, the page says so instead of naming a winner.