Gemma 4 31B vs GPT-6.1 Terra
GPT-6.1 Terra leads Gemma 4 31B on coding, 77.4 to 39.0 on the Vibe Coding Index, and Gemma 4 31B costs 12.5x less per output token ($0.40 vs $5.00 per million). Updated October 29, 2026; 17 benchmarks have a result for both.
Gemma 4 31B or GPT-6.1 Terra: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 39.0 for Gemma 4 31B.
Pick Gemma 4 31B for output tokens 12.5x cheaper ($0.40 vs $5.00 per million).
- Shared results
- 17
- Gemma 4 31B only
- 54
- GPT-6.1 Terra only
- 19
- 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
GPT-6.1 Terra
GPT-6.1 Terra scores 77.4 against 39.0.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Terra has a AA Intelligence Index result, 51.0.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemma 4 31B has a AA Agentic Index result, 4.2.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6.1 Terra has a Design Arena: websites result, 1283.
Directional only
General
Vals Index
No call
Only GPT-6.1 Terra has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
GPT-6.1 Terra
GPT-6.1 Terra takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0003, GPT-6.1 Terra $0.0035 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Agentic work, 53.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench browser: Gemma 4 31B 0.0% against GPT-6.1 Terra 93.1%, 93.1 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against GPT-6.1 Terra $5.00 per million output tokens, 12.5x apart.
- Context window
- Gemma 4 31B takes 262K tokens, GPT-6.1 Terra 1.05M.
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 | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 17 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | 94.3% | GPT-6.1 Terra |
| LMArena WebDev | 1369 | 1673 | GPT-6.1 Terra |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 49.5% | Only GPT-6.1 Terra measured |
| Vibe Code Bench (Vals AI) | Not measured | 84.0% | Only GPT-6.1 Terra measured |
| SciCode | 45.5% | 55.1% | GPT-6.1 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | Not measured | Only Gemma 4 31B measured |
| WeirdML | 52.3% | Not measured | Only Gemma 4 31B measured |
| ALE-Bench | 925.5 | 2608.8 | GPT-6.1 Terra |
| 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 | 1361 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1381 | 1719 | GPT-6.1 Terra |
| SciCode | 8.9% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 51.0 | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | 143.0 | Not measured | Only Gemma 4 31B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | Not measured | Only Gemma 4 31B measured |
| LiveBench research | 44.4% | 73.9% | GPT-6.1 Terra |
| LiveBench browser | 0.0% | 93.1% | GPT-6.1 Terra |
| LiveBench long agentic | 10.7% | 48.6% | GPT-6.1 Terra |
| Tax Agent Bench (Vals AI) | Not measured | 15.2% | Only GPT-6.1 Terra measured |
| Legal Research Bench (Vals AI) | Not measured | 26.0% | Only GPT-6.1 Terra measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 1.7% | Only GPT-6.1 Terra measured |
| τ²-Bench Telecom | 65.5% | Not measured | Only Gemma 4 31B measured |
| APEX-Agents | Not measured | 68.3% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | 88.7% | GPT-6.1 Terra |
| GPQA Diamond (Artificial Analysis run) | 85.7% | Not measured | Only Gemma 4 31B measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 75.8% | 94.3% | GPT-6.1 Terra |
| Mystery game puzzles | Not measured | 74.0% | Only GPT-6.1 Terra measured |
| EBR-bench | Not measured | 78.1% | Only GPT-6.1 Terra measured |
| LMArena Text: hard prompts | 1448 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: expert | 1465 | 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 |
| Humanity's Last Exam (Scale run) | Not measured | 35.7% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | Not measured | 90.9% | Only GPT-6.1 Terra measured |
| FrontierMath, tier 4 | Not measured | 92.7% | Only GPT-6.1 Terra measured |
| LMArena Text: math | 1464 | 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 index01
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | 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% | 57.3% | GPT-6.1 Terra |
| LMArena Text: science | 1457 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | 1450 | 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 | 56.2% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1283 | Only GPT-6.1 Terra measured |
| Design Arena: UI components | Not measured | 1277 | Only GPT-6.1 Terra measured |
| Design Arena: game dev | Not measured | 1348 | Only GPT-6.1 Terra measured |
| Design Arena: all code categories | Not measured | 1295 | Only GPT-6.1 Terra measured |
| LiveBench design | 58.4% | 82.3% | GPT-6.1 Terra |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 31B | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | Not measured | 60.5% | Only GPT-6.1 Terra measured |
| LiveBench data analysis | 53.3% | 82.3% | GPT-6.1 Terra |
| SAGE (Vals AI) | 82.8% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | Not measured | Only Gemma 4 31B measured |
| Long context reasoning (AA-LCR) | 69.7% | 82.7% | GPT-6.1 Terra |
| DTBench | 82.7% | Not measured | Only Gemma 4 31B measured |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| Furniture assembly | Not measured | 79.2% | Only GPT-6.1 Terra measured |
| LMArena Text | 1443 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: instruction following | 1434 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: creative writing | 1416 | 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 | 1431 | 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 | 1444 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Russian | 1461 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Polish | 1431 | 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 |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | 1110 | 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 | GPT-6.1 Terra | 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 | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 2, 2026 | October 26, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.14 | $1.00 |
| Output $/Mtok | $0.40 | $5.00 |
| Coding index | 39.0 | 77.4 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than GPT-6.1 Terra for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 39.0 for Gemma 4 31B. Pick Gemma 4 31B for output tokens 12.5x cheaper ($0.40 vs $5.00 per million).
Which is cheaper, Gemma 4 31B or GPT-6.1 Terra?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 262K.
How many benchmarks is the Gemma 4 31B vs GPT-6.1 Terra comparison based on?
17 benchmarks have a result for both models as of October 29, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and GPT-6.1 Terra's on 4. Where only one model has a result, the page says so instead of naming a winner.