Gemma 4 31B vs MiniMax M3
Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick MiniMax M3 for coding: it scores 57.8 on the Vibe Coding Index against 38.3 for Gemma 4 31B.
Pick Gemma 4 31B when output tokens cost 3.0x less, or when what matters is ALE-Bench or LiveBench long agentic, where it leads.
- Shared results
- 64
- Gemma 4 31B only
- 4
- MiniMax M3 only
- 52
- Like-for-like categories
- 8 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
MiniMax M3
MiniMax M3 scores 57.8 against 38.3.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 14.7.
Same board, both measured
Agentic work
AA Agentic Index
MiniMax M3
MiniMax M3 leads, 29.5 against 4.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiniMax M3 has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M3 has a MMLU Pro result, 84.2%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M3 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0004, MiniMax M3 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M3 has the number, $0.56.
Directional only
At a glance
- Coding index
- Gemma 4 31B 38.3 from 2 benchmarks, MiniMax M3 57.8 from 2 benchmarks.
- Widest category
- Agentic work, 15.4 points apart on average over 5 shared benchmarks.
- Widest single gap
- AA Agentic Index: Gemma 4 31B 4.2 against MiniMax M3 29.5, 25.3 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against MiniMax M3 $1.20 per million output tokens, 3.0x apart.
- Context window
- Gemma 4 31B takes 262K tokens, MiniMax M3 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 | MiniMax M3 | Ties |
|---|---|---|---|---|
| Coding | 1 | 9 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 1 | 4 | ||
| Reasoning | 5 | 4 | ||
| Math | 3 | 0 | ||
| Knowledge | 3 | 2 | ||
| Web design | 0 | 1 | ||
| General | 23 | 6 | ||
| All shared boards | 36 | 28 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index19
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | 70.9% | MiniMax M3 |
| LMArena WebDev | 1367 | 1482 | MiniMax M3 |
| AA Coding Index | 43.4 | 58.6 | MiniMax M3 |
| LiveCodeBench (Vals AI) | Not measured | 82.2% | Only MiniMax M3 measured |
| SWE-bench Verified (Vals AI) | Not measured | 75.0% | Only MiniMax M3 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 1.0% | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.6% | Only MiniMax M3 measured |
| Code migration (Vals AI) | Not measured | 19.9% | Only MiniMax M3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 53.6% | Only MiniMax M3 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.3% | Only MiniMax M3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 9.2% | Only MiniMax M3 measured |
| SkillsBench (Vals AI) | Not measured | 51.5% | Only MiniMax M3 measured |
| CyberBench (Vals AI) | Not measured | 65.0% | Only MiniMax M3 measured |
| SciCode | 45.5% | 47.1% | MiniMax M3 |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 42.4% | MiniMax M3 |
| FrontierCode | Not measured | 14.7% | Only MiniMax M3 measured |
| WeirdML | 52.3% | Not measured | Only Gemma 4 31B measured |
| ALE-Bench | 925.5 | 640.0 | Gemma 4 31B |
| LMArena Text: coding | 1459 | 1470 | MiniMax M3 |
| LMArena Text: software and IT | 1463 | 1466 | MiniMax M3 |
| LMArena WebDev: React | 1359 | 1478 | MiniMax M3 |
| LMArena WebDev: HTML | 1380 | 1455 | MiniMax M3 |
| LMArena WebDev: from an image | Not measured | 1470 | Only MiniMax M3 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 29.2 | MiniMax M3 |
| Epoch Capabilities Index | 143.0 | 146.9 | MiniMax M3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | 29.5 | MiniMax M3 |
| Design Arena: agents building web apps | Not measured | 1200 | Only MiniMax M3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1197 | Only MiniMax M3 measured |
| Design Arena: agents building mobile apps | Not measured | 1169 | Only MiniMax M3 measured |
| Design Arena: agents building Android apps | Not measured | 1164 | Only MiniMax M3 measured |
| Design Arena: agents building games | Not measured | 1158 | Only MiniMax M3 measured |
| Design Arena: HTML slides | Not measured | 1180 | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | Not measured | 1205 | Only MiniMax M3 measured |
| Design Arena: spreadsheets | Not measured | 1021 | Only MiniMax M3 measured |
| LiveBench research | 44.4% | 68.0% | MiniMax M3 |
| LiveBench browser | 4.0% | 8.0% | MiniMax M3 |
| LiveBench long agentic | 13.3% | 12.4% | Gemma 4 31B |
| Finance Agent (Vals AI) | Not measured | 48.3% | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 20.6% | Only MiniMax M3 measured |
| Legal Research Bench (Vals AI) | Not measured | 29.8% | Only MiniMax M3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 47.8% | Only MiniMax M3 measured |
| τ²-Bench Telecom | 65.5% | 88.9% | MiniMax M3 |
| APEX-Agents | Not measured | 37.7% | Only MiniMax M3 measured |
| OSWorld 2.0 | Not measured | 4.6% | Only MiniMax M3 measured |
| Vending-Bench 2 | Not measured | $2,158 | Only MiniMax M3 measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.7% | Only MiniMax M3 measured |
| LiveBench reasoning | 68.3% | 74.5% | MiniMax M3 |
| MMMU Pro (Vals AI) | Not measured | 81.2% | Only MiniMax M3 measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 92.9% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 39.0% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | 75.8% | 90.9% | MiniMax M3 |
| SimpleBench | Not measured | 45.8% | Only MiniMax M3 measured |
| Chess puzzles | Not measured | 13.0% | Only MiniMax M3 measured |
| Mystery game puzzles | Not measured | 8.0% | Only MiniMax M3 measured |
| LMArena Text: hard prompts | 1448 | 1447 | Gemma 4 31B |
| LMArena Text: expert | 1464 | 1461 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1456 | 1455 | Gemma 4 31B |
| LMArena Vision: diagrams | 1283 | 1266 | Gemma 4 31B |
| LMArena Vision: homework | 1310 | 1268 | Gemma 4 31B |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | 71.1% | Gemma 4 31B |
| ProofBench | Not measured | 18.0% | Only MiniMax M3 measured |
| LMArena Text: math | 1463 | 1429 | Gemma 4 31B |
| LMArena Text: mathematical work | 1465 | 1448 | Gemma 4 31B |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.2% | Only MiniMax M3 measured |
| LegalBench (Vals AI) | Not measured | 85.4% | Only MiniMax M3 measured |
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| CorpFin (Vals AI) | Not measured | 68.1% | Only MiniMax M3 measured |
| TaxEval (Vals AI) | Not measured | 72.7% | Only MiniMax M3 measured |
| MortgageTax (Vals AI) | 61.4% | 68.4% | MiniMax M3 |
| MedCode (Vals AI) | Not measured | 46.3% | Only MiniMax M3 measured |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | 1452 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1451 | 1441 | Gemma 4 31B |
| LMArena Text: legal and government | 1438 | 1437 | Gemma 4 31B |
| LMArena Text: business and finance | 1430 | 1434 | MiniMax M3 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1257 | Only MiniMax M3 measured |
| Design Arena: UI components | Not measured | 1246 | Only MiniMax M3 measured |
| Design Arena: game dev | Not measured | 1210 | Only MiniMax M3 measured |
| Design Arena: data viz | Not measured | 1235 | Only MiniMax M3 measured |
| Design Arena: 3D | Not measured | 1209 | Only MiniMax M3 measured |
| Design Arena: all code categories | Not measured | 1247 | Only MiniMax M3 measured |
| Design Arena: SVG | Not measured | 1161 | Only MiniMax M3 measured |
| Design Arena: ASCII art | Not measured | 1161 | Only MiniMax M3 measured |
| LiveBench design | 58.4% | 66.2% | MiniMax M3 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index236
| Benchmark | Gemma 4 31B | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | 76.2% | MiniMax M3 |
| Public Benefits Bench (Vals AI) | Not measured | 64.1% | Only MiniMax M3 measured |
| SAGE (Vals AI) | 55.0% | 50.6% | Gemma 4 31B |
| MedScribe (Vals AI) | Not measured | 87.3% | Only MiniMax M3 measured |
| Vals Multimodal Index | Not measured | 60.0% | Only MiniMax M3 measured |
| IFBench | 75.6% | 82.9% | MiniMax M3 |
| Long context reasoning (AA-LCR) | 69.7% | 83.0% | MiniMax M3 |
| DTBench | 82.7% | 78.9% | Gemma 4 31B |
| LMCA | 39.3% | 33.7% | Gemma 4 31B |
| Surface Evolver Bench | 30.6% | 55.0% | MiniMax M3 |
| LMArena Text | 1443 | 1433 | Gemma 4 31B |
| LMArena Text: instruction following | 1433 | 1433 | Gemma 4 31B |
| LMArena Text: creative writing | 1417 | 1404 | Gemma 4 31B |
| LMArena Vision | 1276 | 1251 | Gemma 4 31B |
| LMArena Text: English | 1451 | 1443 | Gemma 4 31B |
| LMArena Text: non-English | 1430 | 1420 | Gemma 4 31B |
| LMArena Text: Chinese | 1475 | 1466 | Gemma 4 31B |
| LMArena Text: German | Not measured | 1428 | Only MiniMax M3 measured |
| LMArena Text: Japanese | Not measured | 1380 | Only MiniMax M3 measured |
| LMArena Text: Korean | Not measured | 1373 | Only MiniMax M3 measured |
| LMArena Text: French | 1436 | 1444 | MiniMax M3 |
| LMArena Text: Spanish | 1442 | 1433 | Gemma 4 31B |
| LMArena Text: Russian | 1460 | 1426 | Gemma 4 31B |
| LMArena Text: Polish | 1433 | 1423 | Gemma 4 31B |
| LMArena Text: multi-turn | 1452 | 1443 | Gemma 4 31B |
| LMArena Text: longer queries | 1446 | 1446 | Gemma 4 31B |
| LMArena Text: writing and language | 1432 | 1419 | Gemma 4 31B |
| LMArena Text: entertainment and media | 1405 | 1403 | Gemma 4 31B |
| LMArena Vision: English | 1271 | 1263 | Gemma 4 31B |
| LMArena Vision: Chinese | 1326 | 1311 | Gemma 4 31B |
| LMArena Vision: reading text | 1282 | 1259 | Gemma 4 31B |
| LMArena Vision: humor | 1280 | 1235 | Gemma 4 31B |
| LMArena Vision: captioning | 1218 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1226 | 1197 | Gemma 4 31B |
| LMArena Vision: creative writing | 1285 | 1234 | Gemma 4 31B |
| LMArena Document | 1425 | 1435 | MiniMax M3 |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | MiniMax M3 | 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 | MiniMax M3 |
|---|---|---|
| Maker | MiniMax | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | May 31, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.20 | $0.30 |
| Output $/Mtok | $0.40 | $1.20 |
| Coding index | 38.3 | 57.8 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $0.56 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than MiniMax M3 for coding?
Pick MiniMax M3 for coding: it scores 57.8 on the Vibe Coding Index against 38.3 for Gemma 4 31B. Pick Gemma 4 31B when output tokens cost 3.0x less, or when what matters is ALE-Bench or LiveBench long agentic, where it leads.
Which is cheaper, Gemma 4 31B or MiniMax M3?
Gemma 4 31B costs $0.20 per million input tokens and $0.40 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M3 only.
Which has the bigger context window, Gemma 4 31B or MiniMax M3?
MiniMax M3, with 1.05M tokens against 262K.
How many benchmarks is the Gemma 4 31B vs MiniMax M3 comparison based on?
64 benchmarks have a result for both models as of October 21, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and MiniMax M3's on 2. Where only one model has a result, the page says so instead of naming a winner.