Gemma 4 31B vs Qwen3 32B
Gemma 4 31B leads Qwen3 32B on the Artificial Analysis Intelligence Index, 14.7 to 7.3, at about the same output price ($0.40 vs $0.40 per million). Updated October 22, 2026; 36 benchmarks have a result for both.
Gemma 4 31B or Qwen3 32B: which to pick
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 36
- Gemma 4 31B only
- 35
- Qwen3 32B only
- 9
- 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 Gemma 4 31B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemma 4 31B
Gemma 4 31B leads, 14.7 against 7.3.
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
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
No call
Gemma 4 31B $0.0003, Qwen3 32B $0.0003 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, Qwen3 32B not benchmarked.
- Widest category
- Agentic work, 35.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Gemma 4 31B 69.7% against Qwen3 32B 0.0%, 69.7 points apart on a 0 to 100 scale.
- Output price
- Both cost $0.40 per million output tokens.
- Context window
- Gemma 4 31B takes 262K tokens, Qwen3 32B 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 | Qwen3 32B | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 7 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 15 | 0 | ||
| All shared boards | 36 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 40.0% | Only Qwen3 32B 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 (Artificial Analysis run) | Not measured | 54.6% | Only Qwen3 32B measured |
| SciCode | 45.5% | 36.0% | Gemma 4 31B |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 3.0% | Gemma 4 31B |
| WeirdML | 52.3% | Not measured | Only Gemma 4 31B measured |
| ALE-Bench | 925.5 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: coding | 1459 | 1357 | Gemma 4 31B |
| LMArena Text: software and IT | 1463 | 1366 | 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 |
| SciCode | 8.9% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 7.3 | Gemma 4 31B |
| Epoch Capabilities Index | 143.0 | 138.4 | Gemma 4 31B |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 31B | Qwen3 32B | 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% | 29.8% | Gemma 4 31B |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 48.7% | Only Qwen3 32B measured |
| BrowseComp-Plus | Not measured | 10.7% | Only Qwen3 32B measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 66.8% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 7.4% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 75.8% | 65.7% | Gemma 4 31B |
| LMArena Text: hard prompts | 1448 | 1334 | Gemma 4 31B |
| LMArena Text: expert | 1464 | 1362 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1456 | 1350 | 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 |
| Kagi LLM Benchmark | 63.5% | 48.7% | Gemma 4 31B |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 73.0 | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.0% | Only Qwen3 32B measured |
| OTIS Mock AIME | 73.3% | 66.9% | Gemma 4 31B |
| LMArena Text: math | 1463 | 1399 | Gemma 4 31B |
| LMArena Text: mathematical work | 1465 | 1420 | Gemma 4 31B |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 79.8% | Only Qwen3 32B measured |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | 1372 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1451 | 1368 | Gemma 4 31B |
| LMArena Text: legal and government | 1438 | 1324 | Gemma 4 31B |
| LMArena Text: business and finance | 1430 | 1318 | Gemma 4 31B |
| FACTS Benchmark Suite | 45.3% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Qwen3 32B | Leader |
|---|---|---|---|
| LiveBench design | 58.4% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
| Benchmark | Gemma 4 31B | Qwen3 32B | 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% | 36.3% | Gemma 4 31B |
| Long context reasoning (AA-LCR) | 69.7% | 0.0% | Gemma 4 31B |
| DTBench | 82.7% | 67.5% | Gemma 4 31B |
| LMCA | 39.3% | 17.3% | Gemma 4 31B |
| Fiction.LiveBench | Not measured | 74.2% | Only Qwen3 32B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | 1340 | Gemma 4 31B |
| LMArena Text: instruction following | 1433 | 1305 | Gemma 4 31B |
| LMArena Text: creative writing | 1417 | 1297 | Gemma 4 31B |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | 1359 | Gemma 4 31B |
| LMArena Text: non-English | 1430 | 1317 | Gemma 4 31B |
| LMArena Text: Chinese | 1475 | 1357 | Gemma 4 31B |
| LMArena Text: German | Not measured | 1341 | Only Qwen3 32B measured |
| LMArena Text: French | 1436 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Spanish | 1442 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Russian | 1460 | 1311 | Gemma 4 31B |
| LMArena Text: Polish | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1452 | 1331 | Gemma 4 31B |
| LMArena Text: longer queries | 1446 | 1327 | Gemma 4 31B |
| LMArena Text: writing and language | 1432 | 1298 | Gemma 4 31B |
| LMArena Text: entertainment and media | 1405 | 1279 | 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 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | Qwen3 32B | 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 | Qwen3 32B |
|---|---|---|
| Maker | Qwen | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | April 28, 2025 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.14 | $0.14 |
| Output $/Mtok | $0.40 | $0.40 |
| Coding index | 39.0 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than Qwen3 32B for coding?
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemma 4 31B or Qwen3 32B?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or Qwen3 32B?
Gemma 4 31B, with 262K tokens against 131K.
How many benchmarks is the Gemma 4 31B vs Qwen3 32B comparison based on?
36 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Qwen3 32B's on 0. Where only one model has a result, the page says so instead of naming a winner.