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o1 vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads o1 on the Artificial Analysis Intelligence Index, 46.3 to 15.2, and MiMo-V2.6-Pro costs 69.0x less per output token ($0.87 vs $60.00 per million). Updated October 22, 2026; 27 benchmarks have a result for both.

o1OpenAI
Coding
No data
Overall
44.6
Output $/M
$60.00
0
MiMo-V2.6-ProXiaomi
Coding
65.4
Overall
68.4
Output $/M
$0.87
27
vs boards won of 27 shared

o1 or MiMo-V2.6-Pro: which to pick

Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; o1 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
27
o1 only
42
MiMo-V2.6-Pro only
46
Like-for-like categories
6 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.

At a glance

Coding index
o1 not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
Widest category
Intelligence, 31.1 points apart on average over 1 shared benchmark.
Widest single gap
Humanity's Last Exam (Artificial Analysis run): o1 7.0% against MiMo-V2.6-Pro 49.4%, 42.4 points apart on a 0 to 100 scale.
Output price
o1 $60.00 against MiMo-V2.6-Pro $0.87 per million output tokens, 69.0x apart.
Context window
o1 takes 200K tokens, MiMo-V2.6-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.

Boards won, where both have a result
Categoryo1BarsMiMo-V2.6-ProTies
Coding02
Intelligence01
Reasoning04
Math02
Knowledge04
General014
All shared boards027
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
Aider polyglot61.7%Not measuredOnly o1 measured
LiveBench codingNot measured81.5%Only MiMo-V2.6-Pro measured
LMArena WebDevNot measured1625Only MiMo-V2.6-Pro measured
AA Coding Index39.7Not measuredOnly o1 measured
LiveCodeBench (Vals AI)50.3%Not measuredOnly o1 measured
Terminal-Bench 4 (Vals AI)Not measured31.3%Only MiMo-V2.6-Pro measured
Vibe Code Bench (Vals AI)Not measured85.2%Only MiMo-V2.6-Pro measured
Code migration (Vals AI)Not measured43.0%Only MiMo-V2.6-Pro measured
ProgramBench (Vals AI)Not measured0.5%Only MiMo-V2.6-Pro measured
IOI (Vals AI)Not measured39.3%Only MiMo-V2.6-Pro measured
Terminal-Bench 2.1 (Vals AI)Not measured67.8%Only MiMo-V2.6-Pro measured
SWE-bench Multimodal (Vals AI)Not measured41.3%Only MiMo-V2.6-Pro measured
CyberBench (Vals AI)Not measured72.9%Only MiMo-V2.6-Pro measured
LiveCodeBench (Artificial Analysis run)67.9%Not measuredOnly o1 measured
SciCodeNot measured60.9%Only MiMo-V2.6-Pro measured
Terminal-Bench Hard (Artificial Analysis run)12.9%Not measuredOnly o1 measured
WeirdML46.1%Not measuredOnly o1 measured
ALE-BenchNot measured1158.1Only MiMo-V2.6-Pro measured
LMArena Text: coding13671533MiMo-V2.6-Pro
LMArena Text: software and IT13661528MiMo-V2.6-Pro
LMArena WebDev: ReactNot measured1639Only MiMo-V2.6-Pro measured
LMArena WebDev: HTMLNot measured1616Only MiMo-V2.6-Pro measured
LMArena WebDev: from an imageNot measured1598Only MiMo-V2.6-Pro measured
SciCode4.6%Not measuredOnly o1 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
AA Intelligence Index15.246.3MiMo-V2.6-Pro
Epoch Capabilities Index141.7Not measuredOnly o1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
Agentic work benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
Design Arena: agents building web appsNot measured1290Only MiMo-V2.6-Pro measured
LiveBench researchNot measured76.7%Only MiMo-V2.6-Pro measured
LiveBench browserNot measured88.0%Only MiMo-V2.6-Pro measured
LiveBench long agenticNot measured47.5%Only MiMo-V2.6-Pro measured
SREBench (Vals AI)Not measured3.0%Only MiMo-V2.6-Pro measured
Finance Agent (Vals AI)Not measured57.3%Only MiMo-V2.6-Pro measured
Tax Agent Bench (Vals AI)Not measured32.4%Only MiMo-V2.6-Pro measured
Legal Research Bench (Vals AI)Not measured47.1%Only MiMo-V2.6-Pro measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured13.8%Only MiMo-V2.6-Pro measured
Excel Modeling Benchmark (Vals AI)Not measured62.9%Only MiMo-V2.6-Pro measured
Terminal-Bench-Science (Vals AI)Not measured2.9%Only MiMo-V2.6-Pro measured
τ²-Bench Telecom62.6%Not measuredOnly o1 measured
APEX-AgentsNot measured54.4%Only MiMo-V2.6-Pro measured
METR time horizons51.1%Not measuredOnly o1 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
GPQA Diamond73.2%Not measuredOnly o1 measured
LiveBench reasoningNot measured79.6%Only MiMo-V2.6-Pro measured
MysteryMechanism (Vals AI)Not measured15.3%Only MiMo-V2.6-Pro measured
MMMU Pro (Vals AI)77.4%Not measuredOnly o1 measured
GPQA Diamond (Artificial Analysis run)74.7%Not measuredOnly o1 measured
Humanity's Last Exam (Artificial Analysis run)7.0%49.4%MiMo-V2.6-Pro
GPQA Diamond (Epoch AI run)76.8%Not measuredOnly o1 measured
ARC-AGI30.7%Not measuredOnly o1 measured
SimpleBench40.1%Not measuredOnly o1 measured
Chess puzzles10.0%Not measuredOnly o1 measured
VPCT37.0%Not measuredOnly o1 measured
LMArena Text: hard prompts13711511MiMo-V2.6-Pro
LMArena Text: expert13611541MiMo-V2.6-Pro
LMArena Text: hard prompts in English13721520MiMo-V2.6-Pro
LMArena Vision: diagramsNot measured1281Only MiMo-V2.6-Pro measured
LMArena Vision: homeworkNot measured1264Only MiMo-V2.6-Pro measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
AIME71.5%Not measuredOnly o1 measured
MATH 500 (Vals AI)90.4%Not measuredOnly o1 measured
MGSM (Vals AI)89.3%Not measuredOnly o1 measured
OTIS Mock AIME73.3%Not measuredOnly o1 measured
FrontierMath, tiers 1 to 314.7%Not measuredOnly o1 measured
ProofBenchNot measured70.0%Only MiMo-V2.6-Pro measured
MATH level 594.7%Not measuredOnly o1 measured
LMArena Text: math13881500MiMo-V2.6-Pro
LMArena Text: mathematical work13901511MiMo-V2.6-Pro
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
MMLU Pro83.5%Not measuredOnly o1 measured
LegalBench (Vals AI)80.4%Not measuredOnly o1 measured
TaxEval (Vals AI)74.3%Not measuredOnly o1 measured
MedQA (Vals AI)96.5%Not measuredOnly o1 measured
MedCode (Vals AI)Not measured45.0%Only MiMo-V2.6-Pro measured
MMLU Pro (Artificial Analysis run)84.1%Not measuredOnly o1 measured
SimpleQA Verified41.1%Not measuredOnly o1 measured
GeoBench80.0%Not measuredOnly o1 measured
LMArena Text: science13691506MiMo-V2.6-Pro
LMArena Text: medicine and healthcare13551497MiMo-V2.6-Pro
LMArena Text: legal and government13681485MiMo-V2.6-Pro
LMArena Text: business and finance13281468MiMo-V2.6-Pro
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
Design Arena: websitesNot measured1308Only MiMo-V2.6-Pro measured
Design Arena: UI componentsNot measured1340Only MiMo-V2.6-Pro measured
Design Arena: game devNot measured1314Only MiMo-V2.6-Pro measured
Design Arena: data vizNot measured1336Only MiMo-V2.6-Pro measured
Design Arena: 3DNot measured1330Only MiMo-V2.6-Pro measured
Design Arena: all code categoriesNot measured1317Only MiMo-V2.6-Pro measured
LiveBench designNot measured78.5%Only MiMo-V2.6-Pro measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
Vals IndexNot measured57.8%Only MiMo-V2.6-Pro measured
LiveBench data analysisNot measured72.3%Only MiMo-V2.6-Pro measured
Public Benefits Bench (Vals AI)Not measured68.9%Only MiMo-V2.6-Pro measured
SAGE (Vals AI)Not measured45.0%Only MiMo-V2.6-Pro measured
MedScribe (Vals AI)Not measured88.3%Only MiMo-V2.6-Pro measured
IFBench70.3%Not measuredOnly o1 measured
Long context reasoning (AA-LCR)65.0%86.3%MiMo-V2.6-Pro
DTBench74.7%Not measuredOnly o1 measured
LMCA22.3%Not measuredOnly o1 measured
Fiction.LiveBench83.3%Not measuredOnly o1 measured
Creative writing (Lech Mazur)70.2%Not measuredOnly o1 measured
LMArena Text13661491MiMo-V2.6-Pro
LMArena Text: instruction following13671491MiMo-V2.6-Pro
LMArena Text: creative writing13471466MiMo-V2.6-Pro
LMArena Vision11681263MiMo-V2.6-Pro
LMArena Text: English13721504MiMo-V2.6-Pro
LMArena Text: non-English13581474MiMo-V2.6-Pro
LMArena Text: Chinese13941529MiMo-V2.6-Pro
LMArena Text: German1337Not measuredOnly o1 measured
LMArena Text: Japanese1346Not measuredOnly o1 measured
LMArena Text: Korean1396Not measuredOnly o1 measured
LMArena Text: French1344Not measuredOnly o1 measured
LMArena Text: Spanish1345Not measuredOnly o1 measured
LMArena Text: Russian13561479MiMo-V2.6-Pro
LMArena Text: multi-turn13551466MiMo-V2.6-Pro
LMArena Text: longer queries13781501MiMo-V2.6-Pro
LMArena Text: writing and language13601470MiMo-V2.6-Pro
LMArena Text: entertainment and media13581465MiMo-V2.6-Pro
LMArena Vision: English11621268MiMo-V2.6-Pro
LMArena Vision: Chinese1235Not measuredOnly o1 measured
LMArena Vision: reading textNot measured1270Only MiMo-V2.6-Pro measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for o1 and MiMo-V2.6-Pro
Benchmarko1MiMo-V2.6-ProLeader
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

o1$0.045Fits in one request
MiMo-V2.6-Pro$0.0009Fits in one request

MiMo-V2.6-Pro costs less

Repository review

50K input + 3K output tokens

o1$0.930Fits in one request
MiMo-V2.6-Pro$0.024Fits in one request

MiMo-V2.6-Pro costs less

Agent loop

200K input + 10K output tokens

o1$3.60Exceeds the context window
MiMo-V2.6-Pro$0.096Fits in one request

MiMo-V2.6-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.

Specifications of o1 and MiMo-V2.6-Pro
SpecificationOpenAI o1Xiaomi MiMo-V2.6-Pro
MakerOpenAIXiaomi
WeightsNo public weights listedOpen weights
ReleasedDecember 17, 2024September 21, 2026
Context window200K1.05M
Input $/Mtok$15.00$0.435
Output $/Mtok$60.00$0.87
Coding indexNot benchmarked65.4
Independent measurements behind it04
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is o1 better than MiMo-V2.6-Pro for coding?

Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; o1 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, o1 or MiMo-V2.6-Pro?

o1 costs $15.00 per million input tokens and $60.00 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for neither of them.

Which has the bigger context window, o1 or MiMo-V2.6-Pro?

MiMo-V2.6-Pro, with 1.05M tokens against 200K.

How many benchmarks is the o1 vs MiMo-V2.6-Pro comparison based on?

27 benchmarks have a result for both models as of October 22, 2026. o1's coding index rests on 0 independent benchmarks and MiMo-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.

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