GPT-4o-mini vs MiMo-V2.5
MiMo-V2.5 leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 21.8 to 6.7, and MiMo-V2.5 costs 1.8x less per output token ($0.336 vs $0.60 per million). Updated October 21, 2026; 12 benchmarks have a result for both.
GPT-4o-mini or MiMo-V2.5: which to pick
Only MiMo-V2.5 has a coding score, 50.0 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 12
- GPT-4o-mini only
- 15
- MiMo-V2.5 only
- 68
- 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
No call
Only MiMo-V2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.5
MiMo-V2.5 leads, 21.8 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5 has a AA Agentic Index result, 15.8.
Directional only
Reasoning
GPQA Diamond
MiMo-V2.5
MiMo-V2.5 leads, 81.6% against 44.2%.
Same board, both measured
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
MiMo-V2.5
MiMo-V2.5 leads, 82.9% against 62.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiMo-V2.5 has a Design Arena: websites result, 1266.
Directional only
Long documents
Listed context window
MiMo-V2.5
MiMo-V2.5 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5
GPT-4o-mini $0.0004, MiMo-V2.5 $0.0003 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-4o-mini not benchmarked, MiMo-V2.5 50.0 from 3 benchmarks.
- Widest category
- Coding, 50.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- LiveCodeBench (Vals AI): GPT-4o-mini 26.4% against MiMo-V2.5 81.5%, 55.1 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against MiMo-V2.5 $0.336 per million output tokens, 1.8x apart.
- Context window
- GPT-4o-mini takes 128K tokens, MiMo-V2.5 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-4o-mini | Bars | MiMo-V2.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1438 | Only MiMo-V2.5 measured |
| AA Coding Index | 11.4 | 56.8 | MiMo-V2.5 |
| LiveCodeBench (Vals AI) | 26.4% | 81.5% | MiMo-V2.5 |
| SWE-bench Verified (Vals AI) | Not measured | 71.0% | Only MiMo-V2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 42.2% | Only MiMo-V2.5 measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | 23.4% | Not measured | Only GPT-4o-mini measured |
| SciCode | Not measured | 43.9% | Only MiMo-V2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 41.7% | Only MiMo-V2.5 measured |
| ALE-Bench | Not measured | 514.0 | Only MiMo-V2.5 measured |
| 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 | Not measured | 1425 | Only MiMo-V2.5 measured |
| LMArena WebDev: HTML | Not measured | 1429 | Only MiMo-V2.5 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 21.8 | MiMo-V2.5 |
| Epoch Capabilities Index | 126.5 | Not measured | Only GPT-4o-mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 15.8 | Only MiMo-V2.5 measured |
| Finance Agent (Vals AI) | Not measured | 36.7% | Only MiMo-V2.5 measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.8% | Only MiMo-V2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 9.1% | Only MiMo-V2.5 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 |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | 81.6% | MiMo-V2.5 |
| MMMU Pro (Vals AI) | 56.6% | 80.0% | MiMo-V2.5 |
| GPQA Diamond (Artificial Analysis run) | 42.6% | 84.9% | MiMo-V2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 27.2% | MiMo-V2.5 |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o-mini 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 | 1461 | 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 |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| AIME | 11.5% | Not measured | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | Not measured | Only GPT-4o-mini measured |
| AA Math Index | 14.7 | Not measured | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | 14.7% | Not measured | Only GPT-4o-mini measured |
| ProofBench | Not measured | 16.0% | Only MiMo-V2.5 measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1436 | 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 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | 82.9% | MiMo-V2.5 |
| LegalBench (Vals AI) | Not measured | 78.9% | Only MiMo-V2.5 measured |
| CorpFin (Vals AI) | 45.5% | 59.9% | MiMo-V2.5 |
| TaxEval (Vals AI) | 60.5% | 71.8% | MiMo-V2.5 |
| MortgageTax (Vals AI) | 54.5% | 59.3% | MiMo-V2.5 |
| MedQA (Vals AI) | 72.4% | Not measured | Only GPT-4o-mini measured |
| MedCode (Vals AI) | Not measured | 31.9% | Only MiMo-V2.5 measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | Not measured | Only GPT-4o-mini measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini 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 | 1425 | 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 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1266 | Only MiMo-V2.5 measured |
| Design Arena: UI components | Not measured | 1258 | Only MiMo-V2.5 measured |
| Design Arena: game dev | Not measured | 1249 | Only MiMo-V2.5 measured |
| Design Arena: data viz | Not measured | 1249 | Only MiMo-V2.5 measured |
| Design Arena: 3D | Not measured | 1216 | Only MiMo-V2.5 measured |
| Design Arena: all code categories | Not measured | 1260 | Only MiMo-V2.5 measured |
| Design Arena: SVG | Not measured | 1178 | Only MiMo-V2.5 measured |
| Design Arena: ASCII art | Not measured | 1140 | Only MiMo-V2.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o-mini | MiMo-V2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 43.3% | Only MiMo-V2.5 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 | 31.0% | 67.1% | MiMo-V2.5 |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only MiMo-V2.5 measured |
| DTBench | 54.4% | Not measured | Only GPT-4o-mini measured |
| LMCA | 10.4% | Not measured | Only GPT-4o-mini measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini 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 | 1414 | Only MiMo-V2.5 measured |
| LMArena Text: Russian | Not measured | 1396 | 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 |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | 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
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini 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-4o-mini | Xiaomi MiMo-V2.5 |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | April 22, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.15 | $0.168 |
| Output $/Mtok | $0.60 | $0.336 |
| Coding index | Not benchmarked | 50.0 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.01 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini better than MiMo-V2.5 for coding?
Only MiMo-V2.5 has a coding score, 50.0 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4o-mini or MiMo-V2.5?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Cost per solved task is known for MiMo-V2.5 only.
Which has the bigger context window, GPT-4o-mini or MiMo-V2.5?
MiMo-V2.5, with 1.05M tokens against 128K.
How many benchmarks is the GPT-4o-mini vs MiMo-V2.5 comparison based on?
12 benchmarks have a result for both models as of October 21, 2026. GPT-4o-mini's coding index rests on 0 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.