GPT-5.6 Terra vs MiniMax M2.1
GPT-5.6 Terra leads MiniMax M2.1 on the Artificial Analysis Intelligence Index, 42.1 to 20.9, and MiniMax M2.1 costs 10.0x less per output token ($1.20 vs $12.00 per million). Updated October 23, 2026; 24 benchmarks have a result for both.
GPT-5.6 Terra or MiniMax M2.1: which to pick
Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding.
Pick MiniMax M2.1 for output tokens 10.0x cheaper ($1.20 vs $12.00 per million) and work measured by MMLU Pro or Design Arena: 3D, where it leads.
- Shared results
- 24
- GPT-5.6 Terra only
- 105
- MiniMax M2.1 only
- 10
- 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
No call
Only GPT-5.6 Terra has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 20.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Terra has a AA Agentic Index result, 43.2.
Directional only
Reasoning
GPQA Diamond
GPT-5.6 Terra
GPT-5.6 Terra leads, 90.9% against 78.5%.
Same board, both measured
Math
AIME
No call
Only MiniMax M2.1 has a AIME result, 77.9%.
Directional only
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 86.7%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Terra
GPT-5.6 Terra leads, 1268 against 1201.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.1
GPT-5.6 Terra $0.0080, MiniMax M2.1 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Terra
GPT-5.6 Terra $0.42, MiniMax M2.1 $0.59.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.6 Terra 63.9 from 6 benchmarks, MiniMax M2.1 not benchmarked.
- Widest category
- Coding, 25.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-5.6 Terra 1951.4 against MiniMax M2.1 623.8, 44.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Terra $12.00 against MiniMax M2.1 $1.20 per million output tokens, 10.0x apart.
- Context window
- GPT-5.6 Terra takes 1.05M tokens, MiniMax M2.1 205K.
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-5.6 Terra | Bars | MiniMax M2.1 | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Knowledge | 4 | 1 | ||
| Web design | 6 | 1 | ||
| General | 3 | 0 | ||
| All shared boards | 22 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| LiveBench coding | 86.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev | 1521 | Not measured | Only GPT-5.6 Terra measured |
| AA Coding Index | 76.7 | Not measured | Only GPT-5.6 Terra measured |
| LiveCodeBench (Vals AI) | 85.9% | 81.8% | GPT-5.6 Terra |
| SWE-bench Verified (Vals AI) | 95.4% | 74.8% | GPT-5.6 Terra |
| Terminal-Bench 4 (Vals AI) | 22.7% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench (Vals AI) | 74.6% | Not measured | Only GPT-5.6 Terra measured |
| Code migration (Vals AI) | 47.8% | Not measured | Only GPT-5.6 Terra measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.6 Terra measured |
| IOI (Vals AI) | 87.6% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.8% | Not measured | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | 58.9% | Not measured | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GPT-5.6 Terra measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 81.0% | Only MiniMax M2.1 measured |
| SciCode | 55.0% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | 28.8% | GPT-5.6 Terra |
| Terminal-Bench | Not measured | 36.6% | Only MiniMax M2.1 measured |
| FrontierCode | 41.3% | Not measured | Only GPT-5.6 Terra measured |
| WeirdML | 78.3% | Not measured | Only GPT-5.6 Terra measured |
| ALE-Bench | 1951.4 | 623.8 | GPT-5.6 Terra |
| LMArena Text: coding | 1486 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: software and IT | 1482 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: React | 1511 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: HTML | 1526 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: from an image | 1541 | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 10.8% | Not measured | Only GPT-5.6 Terra measured |
| SWE-Bench Pro V2 | 92.4% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.1 | 20.9 | GPT-5.6 Terra |
| Epoch Capabilities Index | 160.1 | Not measured | Only GPT-5.6 Terra measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Agentic Index | 43.2 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building web apps | 1120 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | 1061 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | 1110 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | 1061 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | 1081 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | 1013 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | 1095 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench research | 60.4% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench browser | 84.0% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench long agentic | 48.4% | Not measured | Only GPT-5.6 Terra measured |
| SREBench (Vals AI) | 9.5% | Not measured | Only GPT-5.6 Terra measured |
| Finance Agent (Vals AI) | 54.4% | Not measured | Only GPT-5.6 Terra measured |
| Tax Agent Bench (Vals AI) | 30.0% | Not measured | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only GPT-5.6 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 66.2% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | 86.3% | 85.4% | GPT-5.6 Terra |
| APEX-Agents | 58.2% | Not measured | Only GPT-5.6 Terra measured |
| BALROG | 53.2% | Not measured | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | $7,343 | Not measured | Only GPT-5.6 Terra 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-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| GPQA Diamond | 90.9% | 78.5% | GPT-5.6 Terra |
| LiveBench reasoning | 90.6% | Not measured | Only GPT-5.6 Terra measured |
| MMMU Pro (Vals AI) | 86.5% | Not measured | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 92.5% | 83.0% | GPT-5.6 Terra |
| Humanity's Last Exam (Artificial Analysis run) | 42.9% | 23.2% | GPT-5.6 Terra |
| GPQA Diamond (Epoch AI run) | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI | 96.5% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI-2 | 83.9% | Not measured | Only GPT-5.6 Terra measured |
| SimpleBench | 48.9% | Not measured | Only GPT-5.6 Terra measured |
| Chess puzzles | 47.0% | Not measured | Only GPT-5.6 Terra measured |
| Mystery game puzzles | 35.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts | 1469 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: expert | 1496 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts in English | 1465 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: diagrams | 1295 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: homework | 1312 | Not measured | Only GPT-5.6 Terra measured |
| Kagi LLM Benchmark | 51.3% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| AIME | Not measured | 77.9% | Only MiniMax M2.1 measured |
| MATH 500 (Vals AI) | Not measured | 89.0% | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | Not measured | 87.8% | Only MiniMax M2.1 measured |
| AA Math Index | Not measured | 82.7 | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 82.7% | Only MiniMax M2.1 measured |
| OTIS Mock AIME | 99.7% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tiers 1 to 3 | 86.0% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | 70.7% | Not measured | Only GPT-5.6 Terra measured |
| ProofBench | 74.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: math | 1466 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: mathematical work | 1478 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | 87.0% | MiniMax M2.1 |
| LegalBench (Vals AI) | 85.1% | 75.5% | GPT-5.6 Terra |
| CaseLaw (Vals AI) | Not measured | 55.8% | Only MiniMax M2.1 measured |
| CorpFin (Vals AI) | 65.3% | 58.9% | GPT-5.6 Terra |
| TaxEval (Vals AI) | 76.2% | 66.3% | GPT-5.6 Terra |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Terra measured |
| MedQA (Vals AI) | Not measured | 91.2% | Only MiniMax M2.1 measured |
| MedCode (Vals AI) | 43.4% | 34.1% | GPT-5.6 Terra |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.5% | Only MiniMax M2.1 measured |
| SimpleQA Verified | 43.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: science | 1452 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: medicine and healthcare | 1432 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: legal and government | 1462 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: business and finance | 1448 | Not measured | Only GPT-5.6 Terra measured |
| FACTS Benchmark Suite | 52.0% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | 1201 | GPT-5.6 Terra |
| Design Arena: UI components | 1256 | 1220 | GPT-5.6 Terra |
| Design Arena: game dev | 1229 | 1134 | GPT-5.6 Terra |
| Design Arena: data viz | 1240 | 1207 | GPT-5.6 Terra |
| Design Arena: 3D | 1135 | 1166 | MiniMax M2.1 |
| Design Arena: all code categories | 1241 | 1190 | GPT-5.6 Terra |
| Design Arena: SVG | 1219 | 1131 | GPT-5.6 Terra |
| Design Arena: ASCII art | 1178 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only GPT-5.6 Terra measured |
| Public Benefits Bench (Vals AI) | 62.4% | Not measured | Only GPT-5.6 Terra measured |
| SAGE (Vals AI) | 47.0% | Not measured | Only GPT-5.6 Terra measured |
| MedScribe (Vals AI) | 82.9% | 80.8% | GPT-5.6 Terra |
| Vals Multimodal Index | 65.1% | Not measured | Only GPT-5.6 Terra measured |
| IFBench | 71.2% | 69.9% | GPT-5.6 Terra |
| Long context reasoning (AA-LCR) | 83.0% | 67.7% | GPT-5.6 Terra |
| DTBench | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| LMCA | 54.9% | Not measured | Only GPT-5.6 Terra measured |
| Surface Evolver Bench | 83.8% | Not measured | Only GPT-5.6 Terra measured |
| Furniture assembly | 54.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text | 1448 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: instruction following | 1455 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: creative writing | 1413 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision | 1271 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: English | 1449 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: non-English | 1441 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Chinese | 1514 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: German | 1461 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | 1453 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | 1423 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: French | 1466 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Spanish | 1448 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Russian | 1453 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Polish | 1447 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | 1453 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: longer queries | 1453 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: writing and language | 1432 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: entertainment and media | 1419 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: English | 1272 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: Chinese | 1337 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | 1278 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: humor | 1236 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | 1248 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Document | 1472 | Not measured | Only GPT-5.6 Terra measured |
| EQ-Bench 4 | 1234 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Terra | MiniMax M2.1 | 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 M2.1 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.1 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-5.6 Terra | MiniMax M2.1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | December 23, 2025 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $2.00 | $0.30 |
| Output $/Mtok | $12.00 | $1.20 |
| Coding index | 63.9 | Not benchmarked |
| Independent measurements behind it | 6 | 1 |
| Cost per solved task | $0.42 | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Terra better than MiniMax M2.1 for coding?
Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 10.0x cheaper ($1.20 vs $12.00 per million) and work measured by MMLU Pro or Design Arena: 3D, where it leads.
Which is cheaper, GPT-5.6 Terra or MiniMax M2.1?
GPT-5.6 Terra costs $2.00 per million input tokens and $12.00 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GPT-5.6 Terra costs $0.42 and MiniMax M2.1 $0.59.
Which has the bigger context window, GPT-5.6 Terra or MiniMax M2.1?
GPT-5.6 Terra, with 1.05M tokens against 205K.
How many benchmarks is the GPT-5.6 Terra vs MiniMax M2.1 comparison based on?
24 benchmarks have a result for both models as of October 23, 2026. GPT-5.6 Terra's coding index rests on 6 independent benchmarks and MiniMax M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.