Gemma 4 31B vs Qwen3.5-27B
Updated October 21, 2026. 49 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Gemma 4 31B for coding: it scores 38.3 on the Vibe Coding Index against 22.6 for Qwen3.5-27B.
Pick Qwen3.5-27B when what matters is LMArena WebDev: HTML or AA Intelligence Index, where it leads.
- Shared results
- 49
- Gemma 4 31B only
- 19
- Qwen3.5-27B only
- 4
- 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
Gemma 4 31B
Gemma 4 31B scores 38.3 against 22.6.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.5-27B
Qwen3.5-27B leads, 22.9 against 14.7.
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
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0004, Qwen3.5-27B $0.0014 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 38.3 from 2 benchmarks, Qwen3.5-27B 22.6 from 1 benchmark.
- Widest category
- Agentic work, 28.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 31B 65.5% against Qwen3.5-27B 93.9%, 28.4 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against Qwen3.5-27B $2.16 per million output tokens, 5.4x apart.
- Context window
- Both take 262K tokens.
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 | Qwen3.5-27B | Ties |
|---|---|---|---|---|
| Coding | 7 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 5 | 2 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 23 | 2 | 1 tie | |
| All shared boards | 41 | 7 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index71
| Benchmark | Gemma 4 31B | Qwen3.5-27B | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1367 | 1358 | Gemma 4 31B |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B measured |
| SciCode | 45.5% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 32.6% | Gemma 4 31B |
| WeirdML | 52.3% | 39.5% | Gemma 4 31B |
| ALE-Bench | 925.5 | 349.4 | Gemma 4 31B |
| LMArena Text: coding | 1459 | 1427 | Gemma 4 31B |
| LMArena Text: software and IT | 1463 | 1431 | Gemma 4 31B |
| LMArena WebDev: React | 1359 | 1346 | Gemma 4 31B |
| LMArena WebDev: HTML | 1380 | 1386 | Qwen3.5-27B |
| 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 31B | Qwen3.5-27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 22.9 | Qwen3.5-27B |
| Epoch Capabilities Index | 143.0 | Not measured | Only Gemma 4 31B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | Qwen3.5-27B | 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% | 93.9% | Qwen3.5-27B |
| Vending-Bench 2 | Not measured | $202 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | Gemma 4 31B | Qwen3.5-27B | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 85.8% | Qwen3.5-27B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 23.9% | Qwen3.5-27B |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts | 1448 | 1415 | Gemma 4 31B |
| LMArena Text: expert | 1464 | 1427 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1456 | 1429 | Gemma 4 31B |
| LMArena Vision: diagrams | 1283 | 1249 | Gemma 4 31B |
| LMArena Vision: homework | 1310 | 1256 | 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 index20
| Benchmark | Gemma 4 31B | Qwen3.5-27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: math | 1463 | 1429 | Gemma 4 31B |
| LMArena Text: mathematical work | 1465 | 1429 | Gemma 4 31B |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemma 4 31B | Qwen3.5-27B | 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 |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | 1437 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1451 | 1425 | Gemma 4 31B |
| LMArena Text: legal and government | 1438 | 1405 | Gemma 4 31B |
| LMArena Text: business and finance | 1430 | 1399 | Gemma 4 31B |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Qwen3.5-27B | 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 index232
| Benchmark | Gemma 4 31B | Qwen3.5-27B | 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% | 75.6% | Tie |
| Long context reasoning (AA-LCR) | 69.7% | 77.7% | Qwen3.5-27B |
| DTBench | 82.7% | 82.4% | Gemma 4 31B |
| LMCA | 39.3% | 34.0% | Gemma 4 31B |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | 1409 | Gemma 4 31B |
| LMArena Text: instruction following | 1433 | 1393 | Gemma 4 31B |
| LMArena Text: creative writing | 1417 | 1362 | Gemma 4 31B |
| LMArena Vision | 1276 | 1241 | Gemma 4 31B |
| LMArena Text: English | 1451 | 1425 | Gemma 4 31B |
| LMArena Text: non-English | 1430 | 1390 | Gemma 4 31B |
| LMArena Text: Chinese | 1475 | 1478 | Qwen3.5-27B |
| LMArena Text: German | Not measured | 1392 | Only Qwen3.5-27B measured |
| LMArena Text: Japanese | Not measured | 1346 | Only Qwen3.5-27B measured |
| LMArena Text: Korean | Not measured | 1359 | Only Qwen3.5-27B measured |
| LMArena Text: French | 1436 | 1410 | Gemma 4 31B |
| LMArena Text: Spanish | 1442 | 1407 | Gemma 4 31B |
| LMArena Text: Russian | 1460 | 1390 | Gemma 4 31B |
| LMArena Text: Polish | 1433 | 1375 | Gemma 4 31B |
| LMArena Text: multi-turn | 1452 | 1410 | Gemma 4 31B |
| LMArena Text: longer queries | 1446 | 1413 | Gemma 4 31B |
| LMArena Text: writing and language | 1432 | 1380 | Gemma 4 31B |
| LMArena Text: entertainment and media | 1405 | 1363 | Gemma 4 31B |
| LMArena Vision: English | 1271 | 1246 | Gemma 4 31B |
| LMArena Vision: Chinese | 1326 | 1301 | Gemma 4 31B |
| LMArena Vision: reading text | 1282 | 1246 | Gemma 4 31B |
| LMArena Vision: humor | 1280 | 1227 | Gemma 4 31B |
| LMArena Vision: captioning | 1218 | 1170 | Gemma 4 31B |
| LMArena Vision: recognizing things | 1226 | 1210 | Gemma 4 31B |
| LMArena Vision: creative writing | 1285 | 1224 | Gemma 4 31B |
| LMArena Document | 1425 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | Qwen3.5-27B | 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 | Qwen3.5-27B |
|---|---|---|
| Maker | Qwen | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | February 25, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.20 | $0.27 |
| Output $/Mtok | $0.40 | $2.16 |
| Coding index | 38.3 | 22.6 |
| 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 Qwen3.5-27B for coding?
Pick Gemma 4 31B for coding: it scores 38.3 on the Vibe Coding Index against 22.6 for Qwen3.5-27B. Pick Qwen3.5-27B when what matters is LMArena WebDev: HTML or AA Intelligence Index, where it leads.
Which is cheaper, Gemma 4 31B or Qwen3.5-27B?
Gemma 4 31B costs $0.20 per million input tokens and $0.40 per million output tokens; Qwen3.5-27B costs $0.27 and $2.16. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or Qwen3.5-27B?
Neither: both take 262K tokens.
How many benchmarks is the Gemma 4 31B vs Qwen3.5-27B comparison based on?
49 benchmarks have a result for both models as of October 21, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.