GPT-6.1 Terra vs MiMo-V2.5
GPT-6.1 Terra leads MiMo-V2.5 on coding, 77.4 to 50.0 on the Vibe Coding Index, and MiMo-V2.5 costs 4.5x less per output token ($1.119 vs $5.00 per million). Updated October 29, 2026; 14 benchmarks have a result for both.
GPT-6.1 Terra or MiMo-V2.5: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 50.0 for MiMo-V2.5.
Pick MiMo-V2.5 for output tokens 4.5x cheaper ($1.119 vs $5.00 per million).
- Shared results
- 14
- GPT-6.1 Terra only
- 22
- MiMo-V2.5 only
- 64
- Like-for-like categories
- 5 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 50.0.
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
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5 has a AA Agentic Index result, 15.8.
Directional only
Reasoning
GPQA Diamond
No call
Only MiMo-V2.5 has a GPQA Diamond result, 81.6%.
Directional only
Knowledge
MMLU Pro
No call
Only MiMo-V2.5 has a MMLU Pro result, 82.9%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1265.
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
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5
GPT-6.1 Terra $0.0035, MiMo-V2.5 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiMo-V2.5 has the number, $0.01.
Directional only
At a glance
- Coding index
- GPT-6.1 Terra 77.4 from 4 benchmarks, MiMo-V2.5 50.0 from 3 benchmarks.
- Widest category
- Coding, 35.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-6.1 Terra 2608.8 against MiMo-V2.5 514.0, 69.8 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Terra $5.00 against MiMo-V2.5 $1.119 per million output tokens, 4.5x apart.
- Context window
- Both take 1.05M tokens.
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 | MiMo-V2.5 | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 4 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 14 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | Leader |
|---|---|---|---|
| LiveBench coding | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1673 | 1438 | GPT-6.1 Terra |
| AA Coding Index | Not measured | 56.8 | Only MiMo-V2.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only MiMo-V2.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 71.0% | Only MiMo-V2.5 measured |
| Terminal-Bench 4 (Vals AI) | 49.5% | Not measured | Only GPT-6.1 Terra measured |
| Vibe Code Bench (Vals AI) | 84.0% | 42.2% | GPT-6.1 Terra |
| Code migration (Vals AI) | Not measured | 14.2% | Only MiMo-V2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 60.7% | Only MiMo-V2.5 measured |
| SciCode | 55.1% | 43.9% | GPT-6.1 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 41.7% | Only MiMo-V2.5 measured |
| ALE-Bench | 2608.8 | 514.0 | GPT-6.1 Terra |
| LMArena Text: coding | Not measured | 1469 | Only MiMo-V2.5 measured |
| LMArena Text: software and IT | Not measured | 1463 | Only MiMo-V2.5 measured |
| LMArena WebDev: React | 1657 | 1425 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1719 | 1430 | GPT-6.1 Terra |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.0 | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 15.8 | Only MiMo-V2.5 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 | 36.7% | Only MiMo-V2.5 measured |
| Tax Agent Bench (Vals AI) | 15.2% | 7.8% | GPT-6.1 Terra |
| Legal Research Bench (Vals AI) | 26.0% | 9.1% | GPT-6.1 Terra |
| Harvey's Legal Agent Benchmark (Vals AI) | 1.7% | Not measured | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 55.1% | Only MiMo-V2.5 measured |
| τ²-Bench Telecom | Not measured | 90.6% | Only MiMo-V2.5 measured |
| APEX-Agents | 68.3% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 81.6% | Only MiMo-V2.5 measured |
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6.1 Terra measured |
| MMMU Pro (Vals AI) | Not measured | 80.0% | Only MiMo-V2.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.9% | Only MiMo-V2.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 46.2% | 27.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6.1 Terra 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 | 1450 | Only MiMo-V2.5 measured |
| LMArena Text: expert | Not measured | 1459 | Only MiMo-V2.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only MiMo-V2.5 measured |
| LMArena Vision: diagrams | Not measured | 1269 | Only MiMo-V2.5 measured |
| LMArena Vision: homework | Not measured | 1262 | Only MiMo-V2.5 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 index6 boards, none shared
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | Leader |
|---|---|---|---|
| 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 | 16.0% | Only MiMo-V2.5 measured |
| LMArena Text: math | Not measured | 1437 | Only MiMo-V2.5 measured |
| LMArena Text: mathematical work | Not measured | 1451 | Only MiMo-V2.5 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 | MiMo-V2.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.9% | Only MiMo-V2.5 measured |
| LegalBench (Vals AI) | Not measured | 78.9% | Only MiMo-V2.5 measured |
| CorpFin (Vals AI) | Not measured | 59.9% | Only MiMo-V2.5 measured |
| TaxEval (Vals AI) | Not measured | 71.8% | Only MiMo-V2.5 measured |
| MortgageTax (Vals AI) | Not measured | 59.3% | Only MiMo-V2.5 measured |
| MedCode (Vals AI) | Not measured | 31.9% | Only MiMo-V2.5 measured |
| SimpleQA Verified | 57.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: science | Not measured | 1440 | Only MiMo-V2.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1432 | Only MiMo-V2.5 measured |
| LMArena Text: legal and government | Not measured | 1424 | Only MiMo-V2.5 measured |
| LMArena Text: business and finance | Not measured | 1432 | Only MiMo-V2.5 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 | MiMo-V2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1283 | 1265 | GPT-6.1 Terra |
| Design Arena: UI components | 1277 | 1252 | GPT-6.1 Terra |
| Design Arena: game dev | 1348 | 1250 | GPT-6.1 Terra |
| Design Arena: data viz | Not measured | 1251 | Only MiMo-V2.5 measured |
| Design Arena: 3D | Not measured | 1213 | Only MiMo-V2.5 measured |
| Design Arena: all code categories | 1295 | 1259 | GPT-6.1 Terra |
| Design Arena: SVG | Not measured | 1179 | Only MiMo-V2.5 measured |
| Design Arena: ASCII art | Not measured | 1140 | Only MiMo-V2.5 measured |
| LiveBench design | 82.3% | Not measured | Only GPT-6.1 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | 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 |
| MedScribe (Vals AI) | Not measured | 72.2% | Only MiMo-V2.5 measured |
| Vals Multimodal Index | Not measured | 52.8% | Only MiMo-V2.5 measured |
| IFBench | Not measured | 67.1% | Only MiMo-V2.5 measured |
| Long context reasoning (AA-LCR) | 82.7% | 73.0% | GPT-6.1 Terra |
| Furniture assembly | 79.2% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text | Not measured | 1428 | Only MiMo-V2.5 measured |
| LMArena Text: instruction following | Not measured | 1435 | Only MiMo-V2.5 measured |
| LMArena Text: creative writing | Not measured | 1393 | Only MiMo-V2.5 measured |
| LMArena Vision | Not measured | 1247 | Only MiMo-V2.5 measured |
| LMArena Text: English | Not measured | 1447 | Only MiMo-V2.5 measured |
| LMArena Text: non-English | Not measured | 1405 | Only MiMo-V2.5 measured |
| LMArena Text: Chinese | Not measured | 1469 | Only MiMo-V2.5 measured |
| LMArena Text: German | Not measured | 1421 | Only MiMo-V2.5 measured |
| LMArena Text: Japanese | Not measured | 1306 | Only MiMo-V2.5 measured |
| LMArena Text: Korean | Not measured | 1361 | Only MiMo-V2.5 measured |
| LMArena Text: French | Not measured | 1448 | Only MiMo-V2.5 measured |
| LMArena Text: Spanish | Not measured | 1415 | Only MiMo-V2.5 measured |
| LMArena Text: Russian | Not measured | 1395 | Only MiMo-V2.5 measured |
| LMArena Text: Polish | Not measured | 1413 | Only MiMo-V2.5 measured |
| LMArena Text: multi-turn | Not measured | 1445 | Only MiMo-V2.5 measured |
| LMArena Text: longer queries | Not measured | 1445 | Only MiMo-V2.5 measured |
| LMArena Text: writing and language | Not measured | 1409 | Only MiMo-V2.5 measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only MiMo-V2.5 measured |
| LMArena Vision: English | Not measured | 1259 | Only MiMo-V2.5 measured |
| LMArena Vision: Chinese | Not measured | 1326 | Only MiMo-V2.5 measured |
| LMArena Vision: reading text | Not measured | 1256 | Only MiMo-V2.5 measured |
| LMArena Vision: humor | Not measured | 1226 | Only MiMo-V2.5 measured |
| LMArena Vision: recognizing things | Not measured | 1189 | Only MiMo-V2.5 measured |
| LMArena Vision: creative writing | Not measured | 1230 | Only MiMo-V2.5 measured |
| MultiChallenge | 74.2% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Terra | MiMo-V2.5 | 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
MiMo-V2.5 costs less
Repository review
50K input + 3K output tokens
MiMo-V2.5 costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.5 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 | Xiaomi MiMo-V2.5 |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | October 26, 2026 | April 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.00 | $0.2595 |
| Output $/Mtok | $5.00 | $1.119 |
| Coding index | 77.4 | 50.0 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | Not computable | $0.01 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Terra better than MiMo-V2.5 for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 50.0 for MiMo-V2.5. Pick MiMo-V2.5 for output tokens 4.5x cheaper ($1.119 vs $5.00 per million).
Which is cheaper, GPT-6.1 Terra or MiMo-V2.5?
GPT-6.1 Terra costs $1.00 per million input tokens and $5.00 per million output tokens; MiMo-V2.5 costs $0.2595 and $1.119. Cost per solved task is known for MiMo-V2.5 only.
Which has the bigger context window, GPT-6.1 Terra or MiMo-V2.5?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-6.1 Terra vs MiMo-V2.5 comparison based on?
14 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 MiMo-V2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.