Grok 4.20 vs MiMo-V2.5-Pro
Grok 4.20 leads MiMo-V2.5-Pro on coding, 33.3 to 31.6 on the Vibe Coding Index, and MiMo-V2.5-Pro costs 2.7x less per output token ($0.9152 vs $2.50 per million). Updated October 22, 2026; 33 benchmarks have a result for both.
Grok 4.20 or MiMo-V2.5-Pro: which to pick
Grok 4.20 and MiMo-V2.5-Pro are level for coding, 33.3 against 31.6 on the Vibe Coding Index, so price and context decide.
Pick MiMo-V2.5-Pro for output tokens 2.7x cheaper ($0.9152 vs $2.50 per million) and a lower cost per solved task ($0.03 against $0.72). Pick Grok 4.20 for a larger context window (2M against 1.05M tokens) and work measured by LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.
- Shared results
- 33
- Grok 4.20 only
- 22
- MiMo-V2.5-Pro only
- 37
- 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
Level: 33.3 against 31.6, inside 2 points.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 26.0 against 25.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5-Pro has a AA Agentic Index result, 21.3.
Directional only
Reasoning
GPQA Diamond
Grok 4.20
Grok 4.20 leads, 88.6% against 82.6%.
Same board, both measured
Math
AIME
No call
Only Grok 4.20 has a AIME result, 96.5%.
Directional only
Knowledge
MMLU Pro
Grok 4.20
Grok 4.20 leads, 86.3% against 84.6%.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 1266 against 1229.
Same board, both measured
Long documents
Listed context window
Grok 4.20
Grok 4.20 takes 2M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5-Pro
Grok 4.20 $0.0025, MiMo-V2.5-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5-Pro
Grok 4.20 $0.72, MiMo-V2.5-Pro $0.03.
Published attempt cost and pass rate
At a glance
- Coding index
- Grok 4.20 33.3 from 2 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
- Widest category
- Agentic work, 12.8 points apart on average over 5 shared benchmarks.
- Widest single gap
- Excel Modeling Benchmark (Vals AI): Grok 4.20 11.7% against MiMo-V2.5-Pro 55.2%, 43.5 points apart on a 0 to 100 scale.
- Output price
- Grok 4.20 $2.50 against MiMo-V2.5-Pro $0.9152 per million output tokens, 2.7x apart.
- Context window
- Grok 4.20 takes 2M tokens, MiMo-V2.5-Pro 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 | Grok 4.20 | Bars | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 1 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 5 | ||
| Reasoning | 2 | 1 | ||
| Knowledge | 4 | 1 | ||
| Web design | 1 | 7 | ||
| General | 3 | 2 | ||
| All shared boards | 11 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1480 | Only MiMo-V2.5-Pro measured |
| AA Coding Index | Not measured | 60.2 | Only MiMo-V2.5-Pro measured |
| LiveCodeBench (Vals AI) | 84.3% | 81.3% | Grok 4.20 |
| SWE-bench Verified (Vals AI) | 72.2% | 74.0% | MiMo-V2.5-Pro |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only MiMo-V2.5-Pro measured |
| Vibe Code Bench (Vals AI) | 4.1% | 34.1% | MiMo-V2.5-Pro |
| Code migration (Vals AI) | 0.3% | 21.6% | MiMo-V2.5-Pro |
| Terminal-Bench 2.1 (Vals AI) | 44.2% | 57.3% | MiMo-V2.5-Pro |
| SciCode | Not measured | 50.6% | Only MiMo-V2.5-Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | 43.2% | MiMo-V2.5-Pro |
| Terminal-Bench | 57.3% | Not measured | Only Grok 4.20 measured |
| WeirdML | 52.3% | Not measured | Only Grok 4.20 measured |
| ALE-Bench | Not measured | 899.8 | Only MiMo-V2.5-Pro measured |
| LMArena Text: coding | Not measured | 1501 | Only MiMo-V2.5-Pro measured |
| LMArena Text: software and IT | Not measured | 1495 | Only MiMo-V2.5-Pro measured |
| LMArena WebDev: React | Not measured | 1469 | Only MiMo-V2.5-Pro measured |
| LMArena WebDev: HTML | Not measured | 1473 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.7 | 26.0 | MiMo-V2.5-Pro |
| Epoch Capabilities Index | 152.1 | Not measured | Only Grok 4.20 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.3 | Only MiMo-V2.5-Pro measured |
| Design Arena: agents building web apps | 1144 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building full-stack apps | 1054 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building mobile apps | 1090 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building Android apps | 1045 | Not measured | Only Grok 4.20 measured |
| Design Arena: agents building Godot games | 1089 | Not measured | Only Grok 4.20 measured |
| Design Arena: HTML slides | 1180 | Not measured | Only Grok 4.20 measured |
| Finance Agent (Vals AI) | 28.5% | 41.5% | MiMo-V2.5-Pro |
| Tax Agent Bench (Vals AI) | 7.0% | 11.5% | MiMo-V2.5-Pro |
| Legal Research Bench (Vals AI) | 13.9% | 15.9% | MiMo-V2.5-Pro |
| Excel Modeling Benchmark (Vals AI) | 11.7% | 55.2% | MiMo-V2.5-Pro |
| τ²-Bench Telecom | 93.0% | 94.2% | MiMo-V2.5-Pro |
| Vending-Bench 2 | $4,663 | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 88.6% | 82.6% | Grok 4.20 |
| MMMU Pro (Vals AI) | 83.5% | Not measured | Only Grok 4.20 measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 86.6% | Grok 4.20 |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 35.7% | MiMo-V2.5-Pro |
| ARC-AGI | 89.5% | Not measured | Only Grok 4.20 measured |
| ARC-AGI-2 | 65.1% | Not measured | Only Grok 4.20 measured |
| LMArena Text: hard prompts | Not measured | 1486 | Only MiMo-V2.5-Pro measured |
| LMArena Text: expert | Not measured | 1501 | Only MiMo-V2.5-Pro measured |
| LMArena Text: hard prompts in English | Not measured | 1494 | Only MiMo-V2.5-Pro measured |
| Kagi LLM Benchmark | 75.0% | Not measured | Only Grok 4.20 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AIME | 96.5% | Not measured | Only Grok 4.20 measured |
| ProofBench | Not measured | 22.0% | Only MiMo-V2.5-Pro measured |
| LMArena Text: math | Not measured | 1481 | Only MiMo-V2.5-Pro measured |
| LMArena Text: mathematical work | Not measured | 1491 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 86.3% | 84.6% | Grok 4.20 |
| LegalBench (Vals AI) | 77.7% | 77.1% | Grok 4.20 |
| CaseLaw (Vals AI) | 54.4% | Not measured | Only Grok 4.20 measured |
| CorpFin (Vals AI) | 63.7% | 61.4% | Grok 4.20 |
| TaxEval (Vals AI) | 74.1% | 73.8% | Grok 4.20 |
| MortgageTax (Vals AI) | 45.4% | Not measured | Only Grok 4.20 measured |
| MedQA (Vals AI) | 94.5% | Not measured | Only Grok 4.20 measured |
| MedCode (Vals AI) | 32.2% | 32.5% | MiMo-V2.5-Pro |
| LMArena Text: science | Not measured | 1482 | Only MiMo-V2.5-Pro measured |
| LMArena Text: medicine and healthcare | Not measured | 1473 | Only MiMo-V2.5-Pro measured |
| LMArena Text: legal and government | Not measured | 1474 | Only MiMo-V2.5-Pro measured |
| LMArena Text: business and finance | Not measured | 1466 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1229 | 1266 | MiMo-V2.5-Pro |
| Design Arena: UI components | 1200 | 1246 | MiMo-V2.5-Pro |
| Design Arena: game dev | 1193 | 1261 | MiMo-V2.5-Pro |
| Design Arena: data viz | 1217 | 1257 | MiMo-V2.5-Pro |
| Design Arena: 3D | 1193 | 1243 | MiMo-V2.5-Pro |
| Design Arena: all code categories | 1221 | 1265 | MiMo-V2.5-Pro |
| Design Arena: SVG | 1165 | 1181 | MiMo-V2.5-Pro |
| Design Arena: ASCII art | 1175 | 1156 | Grok 4.20 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.2% | Not measured | Only Grok 4.20 measured |
| MedScribe (Vals AI) | 63.4% | 83.7% | MiMo-V2.5-Pro |
| Vals Multimodal Index | 39.1% | Not measured | Only Grok 4.20 measured |
| IFBench | 81.2% | 79.9% | Grok 4.20 |
| Long context reasoning (AA-LCR) | 69.0% | 79.7% | MiMo-V2.5-Pro |
| DTBench | 90.1% | 84.5% | Grok 4.20 |
| LMCA | 38.7% | 29.5% | Grok 4.20 |
| CL-bench | 22.2% | Not measured | Only Grok 4.20 measured |
| CL-bench Life | 11.9% | Not measured | Only Grok 4.20 measured |
| LMArena Text | Not measured | 1464 | Only MiMo-V2.5-Pro measured |
| LMArena Text: instruction following | Not measured | 1475 | Only MiMo-V2.5-Pro measured |
| LMArena Text: creative writing | Not measured | 1438 | Only MiMo-V2.5-Pro measured |
| LMArena Text: English | Not measured | 1477 | Only MiMo-V2.5-Pro measured |
| LMArena Text: non-English | Not measured | 1448 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Chinese | Not measured | 1507 | Only MiMo-V2.5-Pro measured |
| LMArena Text: German | Not measured | 1459 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Japanese | Not measured | 1410 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Korean | Not measured | 1435 | Only MiMo-V2.5-Pro measured |
| LMArena Text: French | Not measured | 1487 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Spanish | Not measured | 1469 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Russian | Not measured | 1449 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Polish | Not measured | 1464 | Only MiMo-V2.5-Pro measured |
| LMArena Text: multi-turn | Not measured | 1476 | Only MiMo-V2.5-Pro measured |
| LMArena Text: longer queries | Not measured | 1481 | Only MiMo-V2.5-Pro measured |
| LMArena Text: writing and language | Not measured | 1451 | Only MiMo-V2.5-Pro measured |
| LMArena Text: entertainment and media | Not measured | 1438 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.20 | MiMo-V2.5-Pro | 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-Pro costs less
Repository review
50K input + 3K output tokens
MiMo-V2.5-Pro costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.5-Pro 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 | SpaceXAI Grok 4.20 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | xAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | March 31, 2026 | April 22, 2026 |
| Context window | 2M | 1.05M |
| Input $/Mtok | $1.25 | $0.4575 |
| Output $/Mtok | $2.50 | $0.9152 |
| Coding index | 33.3 | 31.6 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.72 | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.20 better than MiMo-V2.5-Pro for coding?
Grok 4.20 and MiMo-V2.5-Pro are level for coding, 33.3 against 31.6 on the Vibe Coding Index, so price and context decide. Pick MiMo-V2.5-Pro for output tokens 2.7x cheaper ($0.9152 vs $2.50 per million) and a lower cost per solved task ($0.03 against $0.72). Pick Grok 4.20 for a larger context window (2M against 1.05M tokens) and work measured by LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.
Which is cheaper, Grok 4.20 or MiMo-V2.5-Pro?
Grok 4.20 costs $1.25 per million input tokens and $2.50 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Per solved SWE-bench Verified task, Grok 4.20 costs $0.72 and MiMo-V2.5-Pro $0.03.
Which has the bigger context window, Grok 4.20 or MiMo-V2.5-Pro?
Grok 4.20, with 2M tokens against 1.05M.
How many benchmarks is the Grok 4.20 vs MiMo-V2.5-Pro comparison based on?
33 benchmarks have a result for both models as of October 22, 2026. Grok 4.20's coding index rests on 2 independent benchmarks and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.