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Qwen3.6 27B vs Qwen3.8 27B

Qwen3.8 27B leads Qwen3.6 27B on coding, 74.2 to 36.8 on the Vibe Coding Index, at about the same output price ($2.55 vs $2.70 per million). Updated October 22, 2026; 15 benchmarks have a result for both.

Replace Qwen3.6 27B Replace Qwen3.8 27B
Qwen3.6 27BQwen
Coding
36.8
Overall
45.3
Output $/M
$2.70
2
Qwen3.8 27BQwen
Coding
74.2
Overall
59.6
Output $/M
$2.55
13
vs boards won of 15 shared

Qwen3.6 27B or Qwen3.8 27B: which to pick

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 36.8 for Qwen3.6 27B.

Pick Qwen3.6 27B for work measured by TaxEval (Vals AI) or MortgageTax (Vals AI), where it leads.

Model AQwen3.6 27BQwen36.8/1002 independent benchmarks$1.30 per solved taskModel BQwen3.8 27BQwen74.2/1004 independent benchmarks$1.26 per solved task
Shared results
15
Qwen3.6 27B only
10
Qwen3.8 27B only
70
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
Qwen3.6 27B 36.8 from 2 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
Widest category
Agentic work, 27.3 points apart on average over 1 shared benchmark.
Widest single gap
Vibe Code Bench (Vals AI): Qwen3.6 27B 11.9% against Qwen3.8 27B 64.8%, 52.9 points apart on a 0 to 100 scale.
Output price
Qwen3.6 27B $2.70 against Qwen3.8 27B $2.55 per million output tokens, 1.1x apart.
Context window
Qwen3.6 27B takes 262K tokens, Qwen3.8 27B 1M.

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 27BBarsQwen3.8 27BTies
Coding04
Intelligence02
Agentic work01
Reasoning02
Knowledge20
General04
All shared boards213
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDevNot measured1593Only Qwen3.8 27B measured
AA Coding Index53.768.1Qwen3.8 27B
LiveCodeBench (Vals AI)Not measured84.0%Only Qwen3.8 27B measured
SWE-bench Verified (Vals AI)70.0%86.0%Qwen3.8 27B
Vibe Code Bench (Vals AI)11.9%64.8%Qwen3.8 27B
Code migration (Vals AI)Not measured14.2%Only Qwen3.8 27B measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)Not measured58.4%Only Qwen3.8 27B measured
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
SciCode42.8%46.6%Qwen3.8 27B
Terminal-Bench Hard (Artificial Analysis run)34.8%Not measuredOnly Qwen3.6 27B measured
LMArena Text: codingNot measured1483Only Qwen3.8 27B measured
LMArena Text: software and ITNot measured1478Only Qwen3.8 27B measured
LMArena WebDev: ReactNot measured1602Only Qwen3.8 27B measured
LMArena WebDev: HTMLNot measured1570Only Qwen3.8 27B measured
LMArena WebDev: from an imageNot measured1577Only Qwen3.8 27B measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
AA Intelligence Index21.433.7Qwen3.8 27B
Epoch Capabilities Index146.2151.7Qwen3.8 27B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
AA Agentic Index18.545.8Qwen3.8 27B
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)Not measured48.5%Only Qwen3.8 27B measured
Tax Agent Bench (Vals AI)Not measured30.9%Only Qwen3.8 27B measured
Legal Research Bench (Vals AI)Not measured36.1%Only Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)Not measured59.7%Only Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
τ²-Bench Telecom94.2%Not measuredOnly Qwen3.6 27B measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
GPQA DiamondNot measured88.9%Only Qwen3.8 27B measured
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)Not measured83.9%Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)84.2%90.5%Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)23.1%33.9%Qwen3.8 27B
GPQA Diamond (Epoch AI run)85.9%Not measuredOnly Qwen3.6 27B measured
ARC-AGINot measured87.5%Only Qwen3.8 27B measured
ARC-AGI-2Not measured42.4%Only Qwen3.8 27B measured
Mystery game puzzles7.0%Not measuredOnly Qwen3.6 27B measured
LMArena Text: hard promptsNot measured1459Only Qwen3.8 27B measured
LMArena Text: expertNot measured1479Only Qwen3.8 27B measured
LMArena Text: hard prompts in EnglishNot measured1461Only Qwen3.8 27B measured
LMArena Vision: diagramsNot measured1285Only Qwen3.8 27B measured
LMArena Vision: homeworkNot measured1295Only Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
OTIS Mock AIME91.1%Not measuredOnly Qwen3.6 27B measured
FrontierMath, tiers 1 to 335.1%Not measuredOnly Qwen3.6 27B measured
ProofBenchNot measured16.0%Only Qwen3.8 27B measured
LMArena Text: mathNot measured1455Only Qwen3.8 27B measured
LMArena Text: mathematical workNot measured1458Only Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index20
Knowledge benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
MMLU ProNot measured84.3%Only Qwen3.8 27B measured
LegalBench (Vals AI)Not measured82.4%Only Qwen3.8 27B measured
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%70.8%Qwen3.6 27B
MortgageTax (Vals AI)68.3%64.9%Qwen3.6 27B
MedCode (Vals AI)Not measured28.7%Only Qwen3.8 27B measured
LMArena Text: scienceNot measured1467Only Qwen3.8 27B measured
LMArena Text: medicine and healthcareNot measured1437Only Qwen3.8 27B measured
LMArena Text: legal and governmentNot measured1447Only Qwen3.8 27B measured
LMArena Text: business and financeNot measured1438Only Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
Neither model has a result on the other 8 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
General benchmarks for Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)45.6%52.4%Qwen3.8 27B
MedScribe (Vals AI)Not measured83.8%Only Qwen3.8 27B measured
IFBench67.6%Not measuredOnly Qwen3.6 27B measured
Long context reasoning (AA-LCR)77.3%82.0%Qwen3.8 27B
DTBench78.1%88.0%Qwen3.8 27B
LMCA34.5%41.4%Qwen3.8 27B
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
LMArena TextNot measured1440Only Qwen3.8 27B measured
LMArena Text: instruction followingNot measured1436Only Qwen3.8 27B measured
LMArena Text: creative writingNot measured1383Only Qwen3.8 27B measured
LMArena VisionNot measured1269Only Qwen3.8 27B measured
LMArena Text: EnglishNot measured1448Only Qwen3.8 27B measured
LMArena Text: non-EnglishNot measured1428Only Qwen3.8 27B measured
LMArena Text: ChineseNot measured1501Only Qwen3.8 27B measured
LMArena Text: GermanNot measured1443Only Qwen3.8 27B measured
LMArena Text: JapaneseNot measured1387Only Qwen3.8 27B measured
LMArena Text: KoreanNot measured1384Only Qwen3.8 27B measured
LMArena Text: FrenchNot measured1465Only Qwen3.8 27B measured
LMArena Text: SpanishNot measured1449Only Qwen3.8 27B measured
LMArena Text: RussianNot measured1415Only Qwen3.8 27B measured
LMArena Text: PolishNot measured1439Only Qwen3.8 27B measured
LMArena Text: multi-turnNot measured1440Only Qwen3.8 27B measured
LMArena Text: longer queriesNot measured1448Only Qwen3.8 27B measured
LMArena Text: writing and languageNot measured1405Only Qwen3.8 27B measured
LMArena Text: entertainment and mediaNot measured1393Only Qwen3.8 27B measured
LMArena Vision: EnglishNot measured1267Only Qwen3.8 27B measured
LMArena Vision: ChineseNot measured1326Only Qwen3.8 27B measured
LMArena Vision: reading textNot measured1281Only Qwen3.8 27B measured
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writingNot measured1237Only Qwen3.8 27B measured
EQ-Bench 41026Not measuredOnly Qwen3.6 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 Qwen3.6 27B and Qwen3.8 27B
BenchmarkQwen3.6 27BQwen3.8 27BLeader
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
Qwen3.8 27B$0.0017Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

Qwen3.6 27B$0.031Fits in one request
Qwen3.8 27B$0.029Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

Qwen3.6 27B$0.117Fits in one request
Qwen3.8 27B$0.111Fits in one request

Qwen3.8 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 Qwen3.6 27B and Qwen3.8 27B
SpecificationQwen3.6 27BQwen3.8 27B
MakerQwenQwen
WeightsOpen weightsOpen weights
ReleasedApril 27, 2026August 14, 2026
Context window262K1M
Input $/Mtok$0.45$0.425
Output $/Mtok$2.70$2.55
Coding index36.874.2
Independent measurements behind it24
Cost per solved task$1.30$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.6 27B better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 36.8 for Qwen3.6 27B. Pick Qwen3.6 27B for work measured by TaxEval (Vals AI) or MortgageTax (Vals AI), where it leads.

Which is cheaper, Qwen3.6 27B or Qwen3.8 27B?

Qwen3.6 27B costs $0.45 per million input tokens and $2.70 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Per solved SWE-bench Verified task, Qwen3.6 27B costs $1.30 and Qwen3.8 27B $1.26.

Which has the bigger context window, Qwen3.6 27B or Qwen3.8 27B?

Qwen3.8 27B, with 1M tokens against 262K.

How many benchmarks is the Qwen3.6 27B vs Qwen3.8 27B comparison based on?

15 benchmarks have a result for both models as of October 22, 2026. Qwen3.6 27B's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 4. 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-qwen3-8-27b" title="Qwen3.6 27B vs Qwen3.8 27B, 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-qwen3-8-27b">LLMBenchmark.ai, Qwen3.6 27B vs Qwen3.8 27B</a></p>