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Qwen3.6 27B vs MiMo-V2.6-Flash

MiMo-V2.6-Flash leads Qwen3.6 27B on coding, 54.7 to 36.8 on the Vibe Coding Index, and MiMo-V2.6-Flash costs 9.6x less per output token ($0.28 vs $2.70 per million). Updated October 22, 2026; 6 benchmarks have a result for both.

Qwen3.6 27BQwen
Coding
36.8
Overall
45.3
Output $/M
$2.70
2
MiMo-V2.6-FlashXiaomi
Coding
54.7
Overall
60.8
Output $/M
$0.28
4
vs boards won of 6 shared

Qwen3.6 27B or MiMo-V2.6-Flash: which to pick

Pick MiMo-V2.6-Flash for coding: it scores 54.7 on the Vibe Coding Index against 36.8 for Qwen3.6 27B.

Pick Qwen3.6 27B for work measured by SAGE (Vals AI) or Long context reasoning (AA-LCR), where it leads.

Shared results
6
Qwen3.6 27B only
18
MiMo-V2.6-Flash only
60
Like-for-like categories
4 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
Qwen3.6 27B 36.8 from 2 benchmarks, MiMo-V2.6-Flash 54.7 from 3 benchmarks.
Widest category
Coding, 37.8 points apart on average over 2 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Qwen3.6 27B 11.9% against MiMo-V2.6-Flash 79.0%, 67.0 points apart on a 0 to 100 scale.
Output price
Qwen3.6 27B $2.70 against MiMo-V2.6-Flash $0.28 per million output tokens, 9.6x apart.
Context window
Qwen3.6 27B takes 262K tokens, MiMo-V2.6-Flash 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
CategoryQwen3.6 27BBarsMiMo-V2.6-FlashTies
Coding02
Intelligence01
Reasoning01
General20
All shared boards24
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
LMArena WebDevNot measured1634Only MiMo-V2.6-Flash measured
AA Coding Index53.7Not measuredOnly Qwen3.6 27B measured
SWE-bench Verified (Vals AI)70.0%Not measuredOnly Qwen3.6 27B measured
Terminal-Bench 4 (Vals AI)Not measured24.2%Only MiMo-V2.6-Flash measured
Vibe Code Bench (Vals AI)11.9%79.0%MiMo-V2.6-Flash
Code migration (Vals AI)Not measured40.9%Only MiMo-V2.6-Flash measured
ProgramBench (Vals AI)Not measured0.5%Only MiMo-V2.6-Flash measured
IOI (Vals AI)Not measured47.7%Only MiMo-V2.6-Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured76.4%Only MiMo-V2.6-Flash measured
CyberBench (Vals AI)Not measured75.4%Only MiMo-V2.6-Flash measured
SciCode42.8%51.3%MiMo-V2.6-Flash
Terminal-Bench Hard (Artificial Analysis run)34.8%Not measuredOnly Qwen3.6 27B measured
ALE-BenchNot measured1244.2Only MiMo-V2.6-Flash measured
LMArena Text: codingNot measured1499Only MiMo-V2.6-Flash measured
LMArena Text: software and ITNot measured1497Only MiMo-V2.6-Flash measured
LMArena WebDev: ReactNot measured1648Only MiMo-V2.6-Flash measured
LMArena WebDev: HTMLNot measured1641Only MiMo-V2.6-Flash measured
LMArena WebDev: from an imageNot measured1596Only MiMo-V2.6-Flash measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
AA Intelligence Index21.437.9MiMo-V2.6-Flash
Epoch Capabilities Index146.2Not measuredOnly Qwen3.6 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Agentic work benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
AA Agentic Index18.5Not measuredOnly Qwen3.6 27B measured
SREBench (Vals AI)Not measured4.2%Only MiMo-V2.6-Flash measured
Finance Agent (Vals AI)Not measured56.3%Only MiMo-V2.6-Flash measured
Tax Agent Bench (Vals AI)Not measured28.5%Only MiMo-V2.6-Flash measured
Legal Research Bench (Vals AI)Not measured38.0%Only MiMo-V2.6-Flash measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured13.3%Only MiMo-V2.6-Flash measured
Excel Modeling Benchmark (Vals AI)Not measured65.5%Only MiMo-V2.6-Flash measured
BioMysteryBench (Vals AI)Not measured69.3%Only MiMo-V2.6-Flash measured
Terminal-Bench-Science (Vals AI)Not measured4.3%Only MiMo-V2.6-Flash measured
Vals Science IndexNot measured31.7%Only MiMo-V2.6-Flash measured
τ²-Bench Telecom94.2%Not measuredOnly Qwen3.6 27B measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
MysteryMechanism (Vals AI)Not measured21.6%Only MiMo-V2.6-Flash measured
GPQA Diamond (Artificial Analysis run)84.2%Not measuredOnly Qwen3.6 27B measured
Humanity's Last Exam (Artificial Analysis run)23.1%35.1%MiMo-V2.6-Flash
GPQA Diamond (Epoch AI run)85.9%Not measuredOnly Qwen3.6 27B measured
Mystery game puzzles7.0%Not measuredOnly Qwen3.6 27B measured
LMArena Text: hard promptsNot measured1475Only MiMo-V2.6-Flash measured
LMArena Text: expertNot measured1496Only MiMo-V2.6-Flash measured
LMArena Text: hard prompts in EnglishNot measured1493Only MiMo-V2.6-Flash measured
LMArena Vision: diagramsNot measured1276Only MiMo-V2.6-Flash measured
LMArena Vision: homeworkNot measured1283Only MiMo-V2.6-Flash measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
OTIS Mock AIME91.1%Not measuredOnly Qwen3.6 27B measured
FrontierMath, tiers 1 to 335.1%Not measuredOnly Qwen3.6 27B measured
ProofBenchNot measured63.0%Only MiMo-V2.6-Flash measured
LMArena Text: mathNot measured1476Only MiMo-V2.6-Flash measured
LMArena Text: mathematical workNot measured1478Only MiMo-V2.6-Flash measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Knowledge benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
CaseLaw (Vals AI)53.2%Not measuredOnly Qwen3.6 27B measured
CorpFin (Vals AI)62.3%Not measuredOnly Qwen3.6 27B measured
TaxEval (Vals AI)71.3%Not measuredOnly Qwen3.6 27B measured
MortgageTax (Vals AI)68.3%Not measuredOnly Qwen3.6 27B measured
MedCode (Vals AI)Not measured41.1%Only MiMo-V2.6-Flash measured
LMArena Text: scienceNot measured1462Only MiMo-V2.6-Flash measured
LMArena Text: medicine and healthcareNot measured1439Only MiMo-V2.6-Flash measured
LMArena Text: legal and governmentNot measured1441Only MiMo-V2.6-Flash measured
LMArena Text: business and financeNot measured1454Only MiMo-V2.6-Flash measured
Neither model has a result on the other 9 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
Vals IndexNot measured54.8%Only MiMo-V2.6-Flash measured
Public Benefits Bench (Vals AI)Not measured67.6%Only MiMo-V2.6-Flash measured
SAGE (Vals AI)45.6%43.5%Qwen3.6 27B
MedScribe (Vals AI)Not measured85.3%Only MiMo-V2.6-Flash measured
IFBench67.6%Not measuredOnly Qwen3.6 27B measured
Long context reasoning (AA-LCR)77.3%74.3%Qwen3.6 27B
DTBench78.1%Not measuredOnly Qwen3.6 27B measured
LMCA34.5%Not measuredOnly Qwen3.6 27B measured
LMArena TextNot measured1453Only MiMo-V2.6-Flash measured
LMArena Text: instruction followingNot measured1452Only MiMo-V2.6-Flash measured
LMArena Text: creative writingNot measured1403Only MiMo-V2.6-Flash measured
LMArena VisionNot measured1256Only MiMo-V2.6-Flash measured
LMArena Text: EnglishNot measured1476Only MiMo-V2.6-Flash measured
LMArena Text: non-EnglishNot measured1431Only MiMo-V2.6-Flash measured
LMArena Text: ChineseNot measured1509Only MiMo-V2.6-Flash measured
LMArena Text: GermanNot measured1458Only MiMo-V2.6-Flash measured
LMArena Text: JapaneseNot measured1359Only MiMo-V2.6-Flash measured
LMArena Text: KoreanNot measured1425Only MiMo-V2.6-Flash measured
LMArena Text: FrenchNot measured1480Only MiMo-V2.6-Flash measured
LMArena Text: SpanishNot measured1453Only MiMo-V2.6-Flash measured
LMArena Text: RussianNot measured1409Only MiMo-V2.6-Flash measured
LMArena Text: PolishNot measured1455Only MiMo-V2.6-Flash measured
LMArena Text: multi-turnNot measured1447Only MiMo-V2.6-Flash measured
LMArena Text: longer queriesNot measured1459Only MiMo-V2.6-Flash measured
LMArena Text: writing and languageNot measured1424Only MiMo-V2.6-Flash measured
LMArena Text: entertainment and mediaNot measured1415Only MiMo-V2.6-Flash measured
LMArena Vision: EnglishNot measured1269Only MiMo-V2.6-Flash measured
LMArena Vision: reading textNot measured1270Only MiMo-V2.6-Flash measured
LMArena Vision: creative writingNot measured1231Only MiMo-V2.6-Flash measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.6 27B and MiMo-V2.6-Flash
BenchmarkQwen3.6 27BMiMo-V2.6-FlashLeader
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

Qwen3.6 27B$0.0018Fits in one request
MiMo-V2.6-Flash$0.0003Fits in one request

MiMo-V2.6-Flash costs less

Repository review

50K input + 3K output tokens

Qwen3.6 27B$0.031Fits in one request
MiMo-V2.6-Flash$0.0078Fits in one request

MiMo-V2.6-Flash costs less

Agent loop

200K input + 10K output tokens

Qwen3.6 27B$0.117Fits in one request
MiMo-V2.6-Flash$0.031Fits in one request

MiMo-V2.6-Flash 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 Qwen3.6 27B and MiMo-V2.6-Flash
SpecificationQwen3.6 27BXiaomi MiMo-V2.6-Flash
MakerQwenXiaomi
WeightsOpen weightsOpen weights
ReleasedApril 27, 2026September 21, 2026
Context window262K1.05M
Input $/Mtok$0.45$0.14
Output $/Mtok$2.70$0.28
Coding index36.854.7
Independent measurements behind it23
Cost per solved task$1.30Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.6 27B better than MiMo-V2.6-Flash for coding?

Pick MiMo-V2.6-Flash for coding: it scores 54.7 on the Vibe Coding Index against 36.8 for Qwen3.6 27B. Pick Qwen3.6 27B for work measured by SAGE (Vals AI) or Long context reasoning (AA-LCR), where it leads.

Which is cheaper, Qwen3.6 27B or MiMo-V2.6-Flash?

Qwen3.6 27B costs $0.45 per million input tokens and $2.70 per million output tokens; MiMo-V2.6-Flash costs $0.14 and $0.28. Cost per solved task is known for Qwen3.6 27B only.

Which has the bigger context window, Qwen3.6 27B or MiMo-V2.6-Flash?

MiMo-V2.6-Flash, with 1.05M tokens against 262K.

How many benchmarks is the Qwen3.6 27B vs MiMo-V2.6-Flash comparison based on?

6 benchmarks have a result for both models as of October 22, 2026. Qwen3.6 27B's coding index rests on 2 independent benchmarks and MiMo-V2.6-Flash's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/qwen3-6-27b-vs-xiaomi-mimo-v2-6-flash" title="Qwen3.6 27B vs MiMo-V2.6-Flash, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/qwen3-6-27b-vs-xiaomi-mimo-v2-6-flash">LLMBenchmark.ai, Qwen3.6 27B vs MiMo-V2.6-Flash</a></p>