GPT-6.1 Terra vs MiniMax M3
GPT-6.1 Terra leads MiniMax M3 on coding, 77.4 to 33.6 on the Vibe Coding Index, and MiniMax M3 costs 4.2x less per output token ($1.20 vs $5.00 per million). Updated October 29, 2026; 20 benchmarks have a result for both.
GPT-6.1 Terra or MiniMax M3: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 33.6 for MiniMax M3, though on 4 benchmarks against 5.
Pick MiniMax M3 for output tokens 4.2x cheaper ($1.20 vs $5.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
- Shared results
- 20
- GPT-6.1 Terra only
- 16
- MiniMax M3 only
- 90
- 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 33.6.
4 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Terra
GPT-6.1 Terra leads, 51.0 against 18.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiniMax M3 has a AA Agentic Index result, 29.5.
Directional only
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
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1256.
Same board, both measured
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 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3
GPT-6.1 Terra $0.0035, 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
- GPT-6.1 Terra 77.4 from 4 benchmarks, MiniMax M3 33.6 from 5 benchmarks.
- Widest category
- Coding, 35.2 points apart on average over 7 shared benchmarks.
- Widest single gap
- Mystery game puzzles: GPT-6.1 Terra 74.0% against MiniMax M3 8.0%, 66.0 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Terra $5.00 against MiniMax M3 $1.20 per million output tokens, 4.2x apart.
- Context window
- GPT-6.1 Terra takes 1.05M 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 | GPT-6.1 Terra | Bars | MiniMax M3 | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 2 | ||
| Reasoning | 3 | 0 | ||
| Math | 1 | 0 | ||
| Web design | 4 | 0 | ||
| General | 0 | 1 | ||
| All shared boards | 17 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench coding | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1673 | 1483 | GPT-6.1 Terra |
| AA Coding Index | Not measured | 58.6 | Only MiniMax M3 measured |
| 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) | 49.5% | 1.0% | GPT-6.1 Terra |
| Vibe Code Bench (Vals AI) | 84.0% | 47.6% | GPT-6.1 Terra |
| 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 | 55.1% | 47.1% | GPT-6.1 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 42.4% | Only MiniMax M3 measured |
| FrontierCode | Not measured | 14.7% | Only MiniMax M3 measured |
| ALE-Bench | 2608.8 | 640.0 | GPT-6.1 Terra |
| LMArena Text: coding | Not measured | 1470 | Only MiniMax M3 measured |
| LMArena Text: software and IT | Not measured | 1466 | Only MiniMax M3 measured |
| LMArena WebDev: React | 1657 | 1479 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1719 | 1455 | GPT-6.1 Terra |
| LMArena WebDev: from an image | Not measured | 1470 | Only MiniMax M3 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.0 | 18.7 | GPT-6.1 Terra |
| Epoch Capabilities Index | Not measured | 146.9 | Only MiniMax M3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 29.5 | Only MiniMax M3 measured |
| Design Arena: agents building web apps | Not measured | 1203 | 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 | 1167 | Only MiniMax M3 measured |
| Design Arena: agents building Android apps | Not measured | 1161 | Only MiniMax M3 measured |
| Design Arena: agents building games | Not measured | 1125 | Only MiniMax M3 measured |
| Design Arena: HTML slides | Not measured | 1077 | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | Not measured | 1161 | Only MiniMax M3 measured |
| Design Arena: spreadsheets | Not measured | 1068 | Only MiniMax M3 measured |
| LiveBench research | 73.9% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench browser | 93.1% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench long agentic | 48.6% | Not measured | Only GPT-6.1 Terra measured |
| Finance Agent (Vals AI) | Not measured | 48.3% | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | 15.2% | 20.6% | MiniMax M3 |
| Legal Research Bench (Vals AI) | 26.0% | 29.8% | MiniMax M3 |
| Harvey's Legal Agent Benchmark (Vals AI) | 1.7% | Not measured | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 47.8% | Only MiniMax M3 measured |
| τ²-Bench Telecom | Not measured | 88.9% | Only MiniMax M3 measured |
| APEX-Agents | 68.3% | 37.7% | GPT-6.1 Terra |
| 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 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.7% | Only MiniMax M3 measured |
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6.1 Terra measured |
| MMMU Pro (Vals AI) | Not measured | 81.2% | Only MiniMax M3 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.9% | Only MiniMax M3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 46.2% | 39.0% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 94.3% | 90.9% | GPT-6.1 Terra |
| SimpleBench | Not measured | 45.8% | Only MiniMax M3 measured |
| Chess puzzles | Not measured | 13.0% | Only MiniMax M3 measured |
| Mystery game puzzles | 74.0% | 8.0% | GPT-6.1 Terra |
| EBR-bench | 78.1% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: hard prompts | Not measured | 1446 | Only MiniMax M3 measured |
| LMArena Text: expert | Not measured | 1461 | Only MiniMax M3 measured |
| LMArena Text: hard prompts in English | Not measured | 1454 | Only MiniMax M3 measured |
| LMArena Vision: diagrams | Not measured | 1266 | Only MiniMax M3 measured |
| LMArena Vision: homework | Not measured | 1268 | Only MiniMax M3 measured |
| Humanity's Last Exam (Scale run) | 35.7% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 71.1% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 90.9% | Not measured | Only GPT-6.1 Terra measured |
| FrontierMath, tier 4 | 92.7% | Not measured | Only GPT-6.1 Terra measured |
| ProofBench | Not measured | 18.0% | Only MiniMax M3 measured |
| LMArena Text: math | Not measured | 1428 | Only MiniMax M3 measured |
| LMArena Text: mathematical work | Not measured | 1447 | Only MiniMax M3 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.2% | Only MiniMax M3 measured |
| LegalBench (Vals AI) | Not measured | 85.4% | Only MiniMax M3 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) | Not measured | 68.4% | Only MiniMax M3 measured |
| MedCode (Vals AI) | Not measured | 46.3% | Only MiniMax M3 measured |
| SimpleQA Verified | 57.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: science | Not measured | 1450 | Only MiniMax M3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1438 | Only MiniMax M3 measured |
| LMArena Text: legal and government | Not measured | 1434 | Only MiniMax M3 measured |
| LMArena Text: business and finance | Not measured | 1433 | Only MiniMax M3 measured |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1283 | 1256 | GPT-6.1 Terra |
| Design Arena: UI components | 1277 | 1240 | GPT-6.1 Terra |
| Design Arena: game dev | 1348 | 1210 | GPT-6.1 Terra |
| Design Arena: data viz | Not measured | 1235 | Only MiniMax M3 measured |
| Design Arena: 3D | Not measured | 1205 | Only MiniMax M3 measured |
| Design Arena: all code categories | 1295 | 1245 | GPT-6.1 Terra |
| Design Arena: SVG | Not measured | 1158 | Only MiniMax M3 measured |
| Design Arena: ASCII art | Not measured | 1157 | Only MiniMax M3 measured |
| LiveBench design | 82.3% | Not measured | Only GPT-6.1 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-6.1 Terra | MiniMax M3 | Leader |
|---|---|---|---|
| Vals Index | 60.5% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench data analysis | 82.3% | Not measured | Only GPT-6.1 Terra measured |
| Public Benefits Bench (Vals AI) | Not measured | 64.1% | Only MiniMax M3 measured |
| SAGE (Vals AI) | Not measured | 85.5% | Only MiniMax M3 measured |
| MedScribe (Vals AI) | Not measured | 87.3% | Only MiniMax M3 measured |
| Vals Multimodal Index | Not measured | 60.0% | Only MiniMax M3 measured |
| IFBench | Not measured | 82.9% | Only MiniMax M3 measured |
| Long context reasoning (AA-LCR) | 82.7% | 83.0% | MiniMax M3 |
| DTBench | Not measured | 78.9% | Only MiniMax M3 measured |
| LMCA | Not measured | 33.7% | Only MiniMax M3 measured |
| Surface Evolver Bench | Not measured | 55.0% | Only MiniMax M3 measured |
| Furniture assembly | 79.2% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text | Not measured | 1431 | Only MiniMax M3 measured |
| LMArena Text: instruction following | Not measured | 1431 | Only MiniMax M3 measured |
| LMArena Text: creative writing | Not measured | 1400 | Only MiniMax M3 measured |
| LMArena Vision | Not measured | 1251 | Only MiniMax M3 measured |
| LMArena Text: English | Not measured | 1442 | Only MiniMax M3 measured |
| LMArena Text: non-English | Not measured | 1418 | Only MiniMax M3 measured |
| LMArena Text: Chinese | Not measured | 1465 | Only MiniMax M3 measured |
| LMArena Text: German | Not measured | 1429 | Only MiniMax M3 measured |
| LMArena Text: Japanese | Not measured | 1376 | Only MiniMax M3 measured |
| LMArena Text: Korean | Not measured | 1371 | Only MiniMax M3 measured |
| LMArena Text: French | Not measured | 1441 | Only MiniMax M3 measured |
| LMArena Text: Spanish | Not measured | 1430 | Only MiniMax M3 measured |
| LMArena Text: Russian | Not measured | 1426 | Only MiniMax M3 measured |
| LMArena Text: Polish | Not measured | 1424 | Only MiniMax M3 measured |
| LMArena Text: multi-turn | Not measured | 1441 | Only MiniMax M3 measured |
| LMArena Text: longer queries | Not measured | 1444 | Only MiniMax M3 measured |
| LMArena Text: writing and language | Not measured | 1416 | Only MiniMax M3 measured |
| LMArena Text: entertainment and media | Not measured | 1401 | Only MiniMax M3 measured |
| LMArena Vision: English | Not measured | 1263 | Only MiniMax M3 measured |
| LMArena Vision: Chinese | Not measured | 1311 | Only MiniMax M3 measured |
| LMArena Vision: reading text | Not measured | 1259 | Only MiniMax M3 measured |
| LMArena Vision: humor | Not measured | 1235 | Only MiniMax M3 measured |
| LMArena Vision: recognizing things | Not measured | 1197 | Only MiniMax M3 measured |
| LMArena Vision: creative writing | Not measured | 1234 | Only MiniMax M3 measured |
| LMArena Document | Not measured | 1435 | Only MiniMax M3 measured |
| MultiChallenge | 74.2% | Not measured | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | Not measured | 1140 | Only MiniMax M3 measured |
| Neither model has a result on the other 9 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Terra | 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
MiniMax M3 costs less
Repository review
50K input + 3K output tokens
MiniMax M3 costs less
Agent loop
200K input + 10K output tokens
MiniMax M3 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 | OpenAI GPT-6.1 Terra | MiniMax M3 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | October 26, 2026 | May 31, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.00 | $0.30 |
| Output $/Mtok | $5.00 | $1.20 |
| Coding index | 77.4 | 33.6 |
| Independent measurements behind it | 4 | 5 |
| Cost per solved task | Not computable | $0.56 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Terra better than MiniMax M3 for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 33.6 for MiniMax M3, though on 4 benchmarks against 5. Pick MiniMax M3 for output tokens 4.2x cheaper ($1.20 vs $5.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Which is cheaper, GPT-6.1 Terra or MiniMax M3?
GPT-6.1 Terra costs $1.00 per million input tokens and $5.00 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, GPT-6.1 Terra or MiniMax M3?
GPT-6.1 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6.1 Terra vs MiniMax M3 comparison based on?
20 benchmarks have a result for both models as of October 29, 2026. GPT-6.1 Terra's coding index rests on 4 independent benchmarks and MiniMax M3's on 5. Where only one model has a result, the page says so instead of naming a winner.