Gemma 4 31B vs Qwen3.6 27B
Gemma 4 31B leads Qwen3.6 27B on coding, 39.0 to 36.8 on the Vibe Coding Index, and Gemma 4 31B costs 6.8x less per output token ($0.40 vs $2.70 per million). Updated October 22, 2026; 18 benchmarks have a result for both.
Gemma 4 31B or Qwen3.6 27B: which to pick
Pick Gemma 4 31B for coding: it scores 39.0 on the Vibe Coding Index against 36.8 for Qwen3.6 27B.
Pick Qwen3.6 27B for work measured by AA Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 18
- Gemma 4 31B only
- 53
- Qwen3.6 27B only
- 6
- 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
Gemma 4 31B
Gemma 4 31B scores 39.0 against 36.8.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.6 27B
Qwen3.6 27B leads, 21.4 against 14.7.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.6 27B
Qwen3.6 27B leads, 18.5 against 4.2.
Same board, both measured
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 $0.0003, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- Agentic work, 21.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Gemma 4 31B 65.5% against Qwen3.6 27B 94.2%, 28.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against Qwen3.6 27B $2.70 per million output tokens, 6.8x 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 | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 2 | 1 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 2 | ||
| General | 4 | 1 | ||
| All shared boards | 8 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| 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 | 53.7 | Qwen3.6 27B |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Qwen3.6 27B measured |
| Vibe Code Bench (Vals AI) | Not measured | 11.9% | Only Qwen3.6 27B measured |
| SciCode | 45.5% | 42.8% | Gemma 4 31B |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 34.8% | 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 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: software and IT | 1463 | Not measured | Only Gemma 4 31B measured |
| 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 index02
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 21.4 | Qwen3.6 27B |
| Epoch Capabilities Index | 143.0 | 146.2 | Qwen3.6 27B |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | 18.5 | Qwen3.6 27B |
| 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% | 94.2% | Qwen3.6 27B |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 84.2% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 23.1% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 75.8% | 85.9% | Qwen3.6 27B |
| Mystery game puzzles | Not measured | 7.0% | Only Qwen3.6 27B measured |
| LMArena Text: hard prompts | 1448 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: expert | 1464 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only Gemma 4 31B measured |
| 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% | 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 index01
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | 91.1% | Qwen3.6 27B |
| FrontierMath, tiers 1 to 3 | Not measured | 35.1% | Only Qwen3.6 27B measured |
| LMArena Text: math | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: mathematical work | 1465 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | 53.2% | Qwen3.6 27B |
| CorpFin (Vals AI) | Not measured | 62.3% | Only Qwen3.6 27B measured |
| TaxEval (Vals AI) | Not measured | 71.3% | Only Qwen3.6 27B measured |
| MortgageTax (Vals AI) | 61.4% | 68.3% | Qwen3.6 27B |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: legal and government | 1438 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: business and finance | 1430 | Not measured | Only Gemma 4 31B measured |
| FACTS Benchmark Suite | 45.3% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Qwen3.6 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 index41
| Benchmark | Gemma 4 31B | Qwen3.6 27B | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 55.0% | 45.6% | Gemma 4 31B |
| IFBench | 75.6% | 67.6% | Gemma 4 31B |
| Long context reasoning (AA-LCR) | 69.7% | 77.3% | Qwen3.6 27B |
| DTBench | 82.7% | 78.1% | Gemma 4 31B |
| LMCA | 39.3% | 34.5% | Gemma 4 31B |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: instruction following | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: creative writing | 1417 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: non-English | 1430 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Chinese | 1475 | Not measured | Only Gemma 4 31B 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 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Polish | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1452 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: longer queries | 1446 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: writing and language | 1432 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: entertainment and media | 1405 | Not measured | Only Gemma 4 31B measured |
| 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 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | Qwen3.6 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 | Qwen3.6 27B |
|---|---|---|
| Maker | Qwen | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | April 27, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.14 | $0.45 |
| Output $/Mtok | $0.40 | $2.70 |
| Coding index | 39.0 | 36.8 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than Qwen3.6 27B for coding?
Pick Gemma 4 31B for coding: it scores 39.0 on the Vibe Coding Index against 36.8 for Qwen3.6 27B. Pick Qwen3.6 27B for work measured by AA Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, Gemma 4 31B or Qwen3.6 27B?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, Gemma 4 31B or Qwen3.6 27B?
Neither: both take 262K tokens.
How many benchmarks is the Gemma 4 31B vs Qwen3.6 27B comparison based on?
18 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.