Gemma 4 31B vs GLM 4.5
Updated October 21, 2026. 34 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 4.5 for coding: it scores 64.2 on the Vibe Coding Index against 38.3 for Gemma 4 31B, though on 1 benchmark against 2.
Pick Gemma 4 31B when output tokens cost 5.5x less, or when the context window is larger, 262K against 131K tokens.
- Shared results
- 34
- Gemma 4 31B only
- 34
- GLM 4.5 only
- 26
- 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 4.5
GLM 4.5 scores 64.2 against 38.3.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemma 4 31B
Gemma 4 31B leads, 14.7 against 12.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemma 4 31B has a AA Agentic Index result, 4.2.
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, 1170.
Directional only
Long documents
Listed context window
Gemma 4 31B
Gemma 4 31B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0004, GLM 4.5 $0.0017 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 38.3 from 2 benchmarks, GLM 4.5 64.2 from 1 benchmark.
- Widest category
- Agentic work, 22.5 points apart on average over 1 shared benchmark.
- Widest single gap
- IFBench: Gemma 4 31B 75.6% against GLM 4.5 44.1%, 31.5 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against GLM 4.5 $2.20 per million output tokens, 5.5x apart.
- Context window
- Gemma 4 31B 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 31B | Bars | GLM 4.5 | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 3 | 1 | ||
| General | 15 | 1 | ||
| All shared boards | 32 | 2 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
| Benchmark | Gemma 4 31B | GLM 4.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 64.2% | Only GLM 4.5 measured |
| LiveBench coding | 49.0% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1367 | Not measured | Only Gemma 4 31B measured |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B 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 | 45.5% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 22.0% | Gemma 4 31B |
| WeirdML | 52.3% | 40.6% | Gemma 4 31B |
| ALE-Bench | 925.5 | 344.8 | Gemma 4 31B |
| LMArena Text: coding | 1459 | 1434 | Gemma 4 31B |
| LMArena Text: software and IT | 1463 | 1440 | Gemma 4 31B |
| LMArena WebDev: React | 1359 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: HTML | 1380 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 31B | GLM 4.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 12.8 | Gemma 4 31B |
| Epoch Capabilities Index | 143.0 | Not measured | Only Gemma 4 31B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 31B | GLM 4.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | Not measured | Only Gemma 4 31B measured |
| LiveBench research | 44.4% | Not measured | Only Gemma 4 31B measured |
| LiveBench browser | 4.0% | Not measured | Only Gemma 4 31B measured |
| LiveBench long agentic | 13.3% | Not measured | Only Gemma 4 31B measured |
| τ²-Bench Telecom | 65.5% | 43.0% | Gemma 4 31B |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemma 4 31B | GLM 4.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 72.2% | Only GLM 4.5 measured |
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 78.2% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 13.0% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts | 1448 | 1429 | Gemma 4 31B |
| LMArena Text: expert | 1464 | 1433 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1456 | 1429 | Gemma 4 31B |
| LMArena Vision: diagrams | 1283 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: homework | 1310 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 31B | 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 | 73.3% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: math | 1463 | 1427 | Gemma 4 31B |
| LMArena Text: mathematical work | 1465 | 1430 | Gemma 4 31B |
| 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 31B | 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 |
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B 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 |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B 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 |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | 1444 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1451 | 1455 | GLM 4.5 |
| LMArena Text: legal and government | 1438 | 1438 | Gemma 4 31B |
| LMArena Text: business and finance | 1430 | 1420 | Gemma 4 31B |
| 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 31B | GLM 4.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1170 | Only GLM 4.5 measured |
| Design Arena: UI components | Not measured | 1144 | Only GLM 4.5 measured |
| Design Arena: game dev | Not measured | 1145 | 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 |
| LiveBench design | 58.4% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index151
| Benchmark | Gemma 4 31B | GLM 4.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 55.0% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | 44.1% | Gemma 4 31B |
| Long context reasoning (AA-LCR) | 69.7% | 52.7% | Gemma 4 31B |
| DTBench | 82.7% | Not measured | Only Gemma 4 31B measured |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Creative writing (Lech Mazur) | Not measured | 73.4% | Only GLM 4.5 measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | 1430 | Gemma 4 31B |
| LMArena Text: instruction following | 1433 | 1404 | Gemma 4 31B |
| LMArena Text: creative writing | 1417 | 1395 | Gemma 4 31B |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | 1437 | Gemma 4 31B |
| LMArena Text: non-English | 1430 | 1417 | Gemma 4 31B |
| LMArena Text: Chinese | 1475 | 1465 | Gemma 4 31B |
| 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 | 1436 | 1418 | Gemma 4 31B |
| LMArena Text: Spanish | 1442 | 1454 | GLM 4.5 |
| LMArena Text: Russian | 1460 | 1413 | Gemma 4 31B |
| LMArena Text: Polish | 1433 | 1422 | Gemma 4 31B |
| LMArena Text: multi-turn | 1452 | 1415 | Gemma 4 31B |
| LMArena Text: longer queries | 1446 | 1412 | Gemma 4 31B |
| LMArena Text: writing and language | 1432 | 1403 | Gemma 4 31B |
| LMArena Text: entertainment and media | 1405 | 1404 | Gemma 4 31B |
| LMArena Vision: English | 1271 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | 1326 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: reading text | 1282 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: humor | 1280 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: captioning | 1218 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | 1285 | Not measured | Only Gemma 4 31B measured |
| LMArena Document | 1425 | Not measured | Only Gemma 4 31B 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 31B | 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 31B costs less
Repository review
50K input + 3K output tokens
Gemma 4 31B costs less
Agent loop
200K input + 10K output tokens
Gemma 4 31B 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 31B | Z.ai GLM 4.5 |
|---|---|---|
| Maker | Z.ai | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | July 25, 2025 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.20 | $0.60 |
| Output $/Mtok | $0.40 | $2.20 |
| Coding index | 38.3 | 64.2 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than GLM 4.5 for coding?
Pick GLM 4.5 for coding: it scores 64.2 on the Vibe Coding Index against 38.3 for Gemma 4 31B, though on 1 benchmark against 2. Pick Gemma 4 31B when output tokens cost 5.5x less, or when the context window is larger, 262K against 131K tokens.
Which is cheaper, Gemma 4 31B or GLM 4.5?
Gemma 4 31B costs $0.20 per million input tokens and $0.40 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 31B or GLM 4.5?
Gemma 4 31B, with 262K tokens against 131K.
How many benchmarks is the Gemma 4 31B vs GLM 4.5 comparison based on?
34 benchmarks have a result for both models as of October 21, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and GLM 4.5's on 1. Where only one model has a result, the page says so instead of naming a winner.