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Qwen3.5-27B vs MiMo-V2.5-Pro

MiMo-V2.5-Pro leads Qwen3.5-27B on the Artificial Analysis Intelligence Index, 26.0 to 22.9, and MiMo-V2.5-Pro costs 1.7x less per output token ($0.9152 vs $1.56 per million). Updated October 22, 2026; 41 benchmarks have a result for both.

Replace Qwen3.5-27B Replace MiMo-V2.5-Pro
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
1
MiMo-V2.5-ProXiaomi
Coding
31.6
Overall
39.3
Output $/M
$0.9152
40
vs boards won of 41 shared

Qwen3.5-27B or MiMo-V2.5-Pro: which to pick

Only MiMo-V2.5-Pro has a coding score, 31.6 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-27B for work measured by LMCA, where it leads.

Model AQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved taskModel BMiMo-V2.5-ProXiaomi31.6/1004 independent benchmarks$0.03 per solved task
Shared results
41
Qwen3.5-27B only
12
MiMo-V2.5-Pro only
29
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.

At a glance

Coding index
Qwen3.5-27B not benchmarked, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
Widest category
Coding, 14.9 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: Qwen3.5-27B 1346 against MiMo-V2.5-Pro 1469, 20.5 points apart on a 0 to 100 scale.
Output price
Qwen3.5-27B $1.56 against MiMo-V2.5-Pro $0.9152 per million output tokens, 1.7x apart.
Context window
Qwen3.5-27B takes 262K 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.

Boards won, where both have a result
CategoryQwen3.5-27BBarsMiMo-V2.5-ProTies
Coding07
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General120
All shared boards140
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
Coding benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
LMArena WebDev13581480MiMo-V2.5-Pro
AA Coding IndexNot measured60.2Only MiMo-V2.5-Pro measured
LiveCodeBench (Vals AI)Not measured81.3%Only MiMo-V2.5-Pro measured
SWE-bench Verified (Vals AI)Not measured74.0%Only MiMo-V2.5-Pro measured
Terminal-Bench 4 (Vals AI)Not measured0.5%Only MiMo-V2.5-Pro measured
Vibe Code Bench (Vals AI)Not measured34.1%Only MiMo-V2.5-Pro measured
Code migration (Vals AI)Not measured21.6%Only MiMo-V2.5-Pro measured
Terminal-Bench 2.1 (Vals AI)Not measured57.3%Only MiMo-V2.5-Pro measured
SciCodeNot measured50.6%Only MiMo-V2.5-Pro measured
Terminal-Bench Hard (Artificial Analysis run)32.6%43.2%MiMo-V2.5-Pro
WeirdML39.5%Not measuredOnly Qwen3.5-27B measured
ALE-Bench349.4899.8MiMo-V2.5-Pro
LMArena Text: coding14271501MiMo-V2.5-Pro
LMArena Text: software and IT14311495MiMo-V2.5-Pro
LMArena WebDev: React13461469MiMo-V2.5-Pro
LMArena WebDev: HTML13861473MiMo-V2.5-Pro
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
AA Intelligence Index22.926.0MiMo-V2.5-Pro
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
AA Agentic IndexNot measured21.3Only MiMo-V2.5-Pro measured
Finance Agent (Vals AI)Not measured41.5%Only MiMo-V2.5-Pro measured
Tax Agent Bench (Vals AI)Not measured11.5%Only MiMo-V2.5-Pro measured
Legal Research Bench (Vals AI)Not measured15.9%Only MiMo-V2.5-Pro measured
Excel Modeling Benchmark (Vals AI)Not measured55.2%Only MiMo-V2.5-Pro measured
τ²-Bench Telecom93.9%94.2%MiMo-V2.5-Pro
Vending-Bench 2$202Not measuredOnly Qwen3.5-27B measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
GPQA DiamondNot measured82.6%Only MiMo-V2.5-Pro measured
GPQA Diamond (Artificial Analysis run)85.8%86.6%MiMo-V2.5-Pro
Humanity's Last Exam (Artificial Analysis run)23.9%35.7%MiMo-V2.5-Pro
LMArena Text: hard prompts14151486MiMo-V2.5-Pro
LMArena Text: expert14271501MiMo-V2.5-Pro
LMArena Text: hard prompts in English14291494MiMo-V2.5-Pro
LMArena Vision: diagrams1249Not measuredOnly Qwen3.5-27B measured
LMArena Vision: homework1256Not measuredOnly Qwen3.5-27B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
ProofBenchNot measured22.0%Only MiMo-V2.5-Pro measured
LMArena Text: math14291481MiMo-V2.5-Pro
LMArena Text: mathematical work14291491MiMo-V2.5-Pro
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
MMLU ProNot measured84.6%Only MiMo-V2.5-Pro measured
LegalBench (Vals AI)Not measured77.1%Only MiMo-V2.5-Pro measured
CorpFin (Vals AI)Not measured61.4%Only MiMo-V2.5-Pro measured
TaxEval (Vals AI)Not measured73.8%Only MiMo-V2.5-Pro measured
MedCode (Vals AI)Not measured32.5%Only MiMo-V2.5-Pro measured
LMArena Text: science14371482MiMo-V2.5-Pro
LMArena Text: medicine and healthcare14251473MiMo-V2.5-Pro
LMArena Text: legal and government14051474MiMo-V2.5-Pro
LMArena Text: business and finance13991466MiMo-V2.5-Pro
Neither model has a result on the other 9 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
Design Arena: websitesNot measured1266Only MiMo-V2.5-Pro measured
Design Arena: UI componentsNot measured1246Only MiMo-V2.5-Pro measured
Design Arena: game devNot measured1261Only MiMo-V2.5-Pro measured
Design Arena: data vizNot measured1257Only MiMo-V2.5-Pro measured
Design Arena: 3DNot measured1243Only MiMo-V2.5-Pro measured
Design Arena: all code categoriesNot measured1265Only MiMo-V2.5-Pro measured
Design Arena: SVGNot measured1181Only MiMo-V2.5-Pro measured
Design Arena: ASCII artNot measured1156Only MiMo-V2.5-Pro measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-ProLeader
MedScribe (Vals AI)Not measured83.7%Only MiMo-V2.5-Pro measured
IFBench75.6%79.9%MiMo-V2.5-Pro
Long context reasoning (AA-LCR)77.7%79.7%MiMo-V2.5-Pro
DTBench82.4%84.5%MiMo-V2.5-Pro
LMCA34.0%29.5%Qwen3.5-27B
LMArena Text14091464MiMo-V2.5-Pro
LMArena Text: instruction following13931475MiMo-V2.5-Pro
LMArena Text: creative writing13621438MiMo-V2.5-Pro
LMArena Vision1241Not measuredOnly Qwen3.5-27B measured
LMArena Text: English14251477MiMo-V2.5-Pro
LMArena Text: non-English13901448MiMo-V2.5-Pro
LMArena Text: Chinese14781507MiMo-V2.5-Pro
LMArena Text: German13921459MiMo-V2.5-Pro
LMArena Text: Japanese13461410MiMo-V2.5-Pro
LMArena Text: Korean13591435MiMo-V2.5-Pro
LMArena Text: French14101487MiMo-V2.5-Pro
LMArena Text: Spanish14071469MiMo-V2.5-Pro
LMArena Text: Russian13901449MiMo-V2.5-Pro
LMArena Text: Polish13751464MiMo-V2.5-Pro
LMArena Text: multi-turn14101476MiMo-V2.5-Pro
LMArena Text: longer queries14131481MiMo-V2.5-Pro
LMArena Text: writing and language13801451MiMo-V2.5-Pro
LMArena Text: entertainment and media13631438MiMo-V2.5-Pro
LMArena Vision: English1246Not measuredOnly Qwen3.5-27B measured
LMArena Vision: Chinese1301Not measuredOnly Qwen3.5-27B measured
LMArena Vision: reading text1246Not measuredOnly Qwen3.5-27B measured
LMArena Vision: humor1227Not measuredOnly Qwen3.5-27B measured
LMArena Vision: captioning1170Not measuredOnly Qwen3.5-27B measured
LMArena Vision: recognizing things1210Not measuredOnly Qwen3.5-27B measured
LMArena Vision: creative writing1224Not measuredOnly Qwen3.5-27B 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
Image generation benchmarks for Qwen3.5-27B and MiMo-V2.5-Pro
BenchmarkQwen3.5-27BMiMo-V2.5-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

Qwen3.5-27B$0.0010Fits in one request
MiMo-V2.5-Pro$0.0009Fits in one request

MiMo-V2.5-Pro costs less

Repository review

50K input + 3K output tokens

Qwen3.5-27B$0.014Fits in one request
MiMo-V2.5-Pro$0.026Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-27B$0.055Fits in one request
MiMo-V2.5-Pro$0.101Fits in one request

Qwen3.5-27B 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 Qwen3.5-27B and MiMo-V2.5-Pro
SpecificationQwen3.5-27BXiaomi MiMo-V2.5-Pro
MakerQwenXiaomi
WeightsOpen weightsOpen weights
ReleasedFebruary 25, 2026April 22, 2026
Context window262K1.05M
Input $/Mtok$0.195$0.4575
Output $/Mtok$1.56$0.9152
Coding indexNot benchmarked31.6
Independent measurements behind it14
Cost per solved taskNot computable$0.03
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-27B better than MiMo-V2.5-Pro for coding?

Only MiMo-V2.5-Pro has a coding score, 31.6 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding. Pick Qwen3.5-27B for work measured by LMCA, where it leads.

Which is cheaper, Qwen3.5-27B or MiMo-V2.5-Pro?

Qwen3.5-27B costs $0.195 per million input tokens and $1.56 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Cost per solved task is known for MiMo-V2.5-Pro only.

Which has the bigger context window, Qwen3.5-27B or MiMo-V2.5-Pro?

MiMo-V2.5-Pro, with 1.05M tokens against 262K.

How many benchmarks is the Qwen3.5-27B vs MiMo-V2.5-Pro comparison based on?

41 benchmarks have a result for both models as of October 22, 2026. Qwen3.5-27B's coding index rests on 1 independent benchmark and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.

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