GPT-6.1 Terra vs MiniMax M2.5
GPT-6.1 Terra leads MiniMax M2.5 on coding, 77.4 to 37.2 on the Vibe Coding Index, and MiniMax M2.5 costs 4.2x less per output token ($1.20 vs $5.00 per million). Updated October 29, 2026; 11 benchmarks have a result for both.
GPT-6.1 Terra or MiniMax M2.5: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 37.2 for MiniMax M2.5.
Pick MiniMax M2.5 for output tokens 4.2x cheaper ($1.20 vs $5.00 per million).
- Shared results
- 11
- GPT-6.1 Terra only
- 25
- MiniMax M2.5 only
- 59
- Like-for-like categories
- 4 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 37.2.
4 and 3 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
Reasoning
GPQA Diamond
No call
Only MiniMax M2.5 has a GPQA Diamond result, 82.1%.
Directional only
Math
AIME
No call
Only MiniMax M2.5 has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.5 has a MMLU Pro result, 80.1%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1222.
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 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.5
GPT-6.1 Terra $0.0035, MiniMax M2.5 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.5 has the number, $0.62.
Directional only
At a glance
- Coding index
- GPT-6.1 Terra 77.4 from 4 benchmarks, MiniMax M2.5 37.2 from 3 benchmarks.
- Widest category
- Coding, 49.0 points apart on average over 5 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-6.1 Terra 84.0% against MiniMax M2.5 14.8%, 69.2 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Terra $5.00 against MiniMax M2.5 $1.20 per million output tokens, 4.2x apart.
- Context window
- GPT-6.1 Terra takes 1.05M tokens, MiniMax M2.5 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-6.1 Terra | Bars | MiniMax M2.5 | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 4 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 75.8% | Only MiniMax M2.5 measured |
| SWE-bench Multilingual | Not measured | 68.3% | Only MiniMax M2.5 measured |
| LiveBench coding | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1673 | 1386 | GPT-6.1 Terra |
| LiveCodeBench (Vals AI) | Not measured | 79.2% | Only MiniMax M2.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 74.2% | Only MiniMax M2.5 measured |
| Terminal-Bench 4 (Vals AI) | 49.5% | Not measured | Only GPT-6.1 Terra measured |
| Vibe Code Bench (Vals AI) | 84.0% | 14.8% | GPT-6.1 Terra |
| SciCode | 55.1% | Not measured | Only GPT-6.1 Terra measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only MiniMax M2.5 measured |
| Terminal-Bench | Not measured | 42.7% | Only MiniMax M2.5 measured |
| ALE-Bench | 2608.8 | 618.2 | GPT-6.1 Terra |
| LMArena Text: coding | Not measured | 1380 | Only MiniMax M2.5 measured |
| LMArena Text: software and IT | Not measured | 1383 | Only MiniMax M2.5 measured |
| LMArena WebDev: React | 1657 | 1374 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1719 | 1414 | GPT-6.1 Terra |
| SWE Atlas: Codebase QnA | Not measured | 10.3% | Only MiniMax M2.5 measured |
| SWE Atlas: Refactoring | Not measured | 19.5% | Only MiniMax M2.5 measured |
| SWE Atlas: Test Writing | Not measured | 18.6% | Only MiniMax M2.5 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.0 | Not measured | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | Not measured | 146.6 | Only MiniMax M2.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| 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 |
| Tax Agent Bench (Vals AI) | 15.2% | Not measured | Only GPT-6.1 Terra measured |
| Legal Research Bench (Vals AI) | 26.0% | Not measured | Only GPT-6.1 Terra measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 1.7% | Not measured | Only GPT-6.1 Terra measured |
| τ²-Bench Telecom | Not measured | 95.3% | Only MiniMax M2.5 measured |
| APEX-Agents | 68.3% | Not measured | Only GPT-6.1 Terra measured |
| Vending-Bench 2 | Not measured | -$23 | Only MiniMax M2.5 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.1% | Only MiniMax M2.5 measured |
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6.1 Terra measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.8% | Only MiniMax M2.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 46.2% | 20.5% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| ARC-AGI | Not measured | 63.7% | Only MiniMax M2.5 measured |
| ARC-AGI-2 | Not measured | 4.9% | Only MiniMax M2.5 measured |
| Mystery game puzzles | 74.0% | Not measured | Only GPT-6.1 Terra measured |
| EBR-bench | 78.1% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: hard prompts | Not measured | 1372 | Only MiniMax M2.5 measured |
| LMArena Text: expert | Not measured | 1379 | Only MiniMax M2.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1383 | Only MiniMax M2.5 measured |
| Kagi LLM Benchmark | Not measured | 55.2% | Only MiniMax M2.5 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 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 88.8% | Only MiniMax M2.5 measured |
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Terra measured |
| 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 | 4.0% | Only MiniMax M2.5 measured |
| LMArena Text: math | Not measured | 1378 | Only MiniMax M2.5 measured |
| LMArena Text: mathematical work | Not measured | 1379 | Only MiniMax M2.5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 80.1% | Only MiniMax M2.5 measured |
| LegalBench (Vals AI) | Not measured | 80.0% | Only MiniMax M2.5 measured |
| CaseLaw (Vals AI) | Not measured | 53.5% | Only MiniMax M2.5 measured |
| CorpFin (Vals AI) | Not measured | 59.6% | Only MiniMax M2.5 measured |
| TaxEval (Vals AI) | Not measured | 68.2% | Only MiniMax M2.5 measured |
| MedQA (Vals AI) | Not measured | 92.5% | Only MiniMax M2.5 measured |
| SimpleQA Verified | 57.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: science | Not measured | 1369 | Only MiniMax M2.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1357 | Only MiniMax M2.5 measured |
| LMArena Text: legal and government | Not measured | 1366 | Only MiniMax M2.5 measured |
| LMArena Text: business and finance | Not measured | 1356 | Only MiniMax M2.5 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 M2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1283 | 1222 | GPT-6.1 Terra |
| Design Arena: UI components | 1277 | 1167 | GPT-6.1 Terra |
| Design Arena: game dev | 1348 | 1176 | GPT-6.1 Terra |
| Design Arena: data viz | Not measured | 1172 | Only MiniMax M2.5 measured |
| Design Arena: 3D | Not measured | 1167 | Only MiniMax M2.5 measured |
| Design Arena: all code categories | 1295 | 1205 | GPT-6.1 Terra |
| Design Arena: SVG | Not measured | 1146 | Only MiniMax M2.5 measured |
| LiveBench design | 82.3% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | 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 |
| IFBench | Not measured | 71.6% | Only MiniMax M2.5 measured |
| Long context reasoning (AA-LCR) | 82.7% | 73.3% | GPT-6.1 Terra |
| CL-bench | Not measured | 11.4% | Only MiniMax M2.5 measured |
| Furniture assembly | 79.2% | Not measured | Only GPT-6.1 Terra measured |
| CL-bench Life | Not measured | 6.3% | Only MiniMax M2.5 measured |
| LMArena Text | Not measured | 1359 | Only MiniMax M2.5 measured |
| LMArena Text: instruction following | Not measured | 1353 | Only MiniMax M2.5 measured |
| LMArena Text: creative writing | Not measured | 1330 | Only MiniMax M2.5 measured |
| LMArena Text: English | Not measured | 1380 | Only MiniMax M2.5 measured |
| LMArena Text: non-English | Not measured | 1338 | Only MiniMax M2.5 measured |
| LMArena Text: Chinese | Not measured | 1393 | Only MiniMax M2.5 measured |
| LMArena Text: German | Not measured | 1360 | Only MiniMax M2.5 measured |
| LMArena Text: Japanese | Not measured | 1172 | Only MiniMax M2.5 measured |
| LMArena Text: Korean | Not measured | 1233 | Only MiniMax M2.5 measured |
| LMArena Text: French | Not measured | 1363 | Only MiniMax M2.5 measured |
| LMArena Text: Spanish | Not measured | 1353 | Only MiniMax M2.5 measured |
| LMArena Text: Russian | Not measured | 1359 | Only MiniMax M2.5 measured |
| LMArena Text: Polish | Not measured | 1334 | Only MiniMax M2.5 measured |
| LMArena Text: multi-turn | Not measured | 1364 | Only MiniMax M2.5 measured |
| LMArena Text: longer queries | Not measured | 1366 | Only MiniMax M2.5 measured |
| LMArena Text: writing and language | Not measured | 1345 | Only MiniMax M2.5 measured |
| LMArena Text: entertainment and media | Not measured | 1328 | Only MiniMax M2.5 measured |
| MultiChallenge | 74.2% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Terra | MiniMax M2.5 | 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 M2.5 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.5 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.5 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 M2.5 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | October 26, 2026 | February 12, 2026 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $1.00 | $0.30 |
| Output $/Mtok | $5.00 | $1.20 |
| Coding index | 77.4 | 37.2 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | Not computable | $0.62 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Terra better than MiniMax M2.5 for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 37.2 for MiniMax M2.5. Pick MiniMax M2.5 for output tokens 4.2x cheaper ($1.20 vs $5.00 per million).
Which is cheaper, GPT-6.1 Terra or MiniMax M2.5?
GPT-6.1 Terra costs $1.00 per million input tokens and $5.00 per million output tokens; MiniMax M2.5 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.5 only.
Which has the bigger context window, GPT-6.1 Terra or MiniMax M2.5?
GPT-6.1 Terra, with 1.05M tokens against 205K.
How many benchmarks is the GPT-6.1 Terra vs MiniMax M2.5 comparison based on?
11 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 M2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.