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Phi 4 vs Qwen3.6 27B

Updated October 21, 2026. 10 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
0
Qwen3.6 27BQwen
Coding
36.8
Overall
21.4
Output $/M
$2.70
10
vs boards won of 10 shared

Decision reading

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding.

Phi 4 has the edge where output tokens cost 19.3x less.

Shared results
10
Phi 4 only
35
Qwen3.6 27B only
14
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Phi 4 not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
Widest category
Agentic work, 94.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Phi 4 0.0% against Qwen3.6 27B 94.2%, 94.2 points apart on a 0 to 100 scale.
Output price
Phi 4 $0.14 against Qwen3.6 27B $2.70 per million output tokens, 19.3x apart.
Context window
Phi 4 takes 16K tokens, Qwen3.6 27B 262K.

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
CategoryPhi 4BarsQwen3.6 27BTies
Coding01
Intelligence02
Agentic work01
Reasoning03
Math01
General02
All shared boards010
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
AA Coding IndexNot measured53.7Only Qwen3.6 27B measured
SWE-bench Verified (Vals AI)Not measured70.0%Only Qwen3.6 27B measured
Vibe Code Bench (Vals AI)Not measured11.9%Only Qwen3.6 27B measured
LiveCodeBench (Artificial Analysis run)23.1%Not measuredOnly Phi 4 measured
SciCodeNot measured42.8%Only Qwen3.6 27B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%34.8%Qwen3.6 27B
LMArena Text: coding1231Not measuredOnly Phi 4 measured
LMArena Text: software and IT1228Not measuredOnly Phi 4 measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
AA Intelligence Index5.921.4Qwen3.6 27B
Epoch Capabilities Index130.5146.2Qwen3.6 27B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
AA Agentic IndexNot measured18.5Only Qwen3.6 27B measured
τ²-Bench Telecom0.0%94.2%Qwen3.6 27B
BALROG11.6%Not measuredOnly Phi 4 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
GPQA Diamond (Artificial Analysis run)57.5%84.2%Qwen3.6 27B
Humanity's Last Exam (Artificial Analysis run)3.8%23.1%Qwen3.6 27B
GPQA Diamond (Epoch AI run)56.1%85.9%Qwen3.6 27B
Mystery game puzzlesNot measured7.0%Only Qwen3.6 27B measured
LMArena Text: hard prompts1220Not measuredOnly Phi 4 measured
LMArena Text: expert1203Not measuredOnly Phi 4 measured
LMArena Text: hard prompts in English1230Not measuredOnly Phi 4 measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
AA Math Index18.0Not measuredOnly Phi 4 measured
AIME 2025 (Artificial Analysis run)18.0%Not measuredOnly Phi 4 measured
OTIS Mock AIME13.8%91.1%Qwen3.6 27B
FrontierMath, tiers 1 to 3Not measured35.1%Only Qwen3.6 27B measured
MATH level 564.9%Not measuredOnly Phi 4 measured
LMArena Text: math1246Not measuredOnly Phi 4 measured
LMArena Text: mathematical work1254Not measuredOnly Phi 4 measured
Neither model has a result on the other 6 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Knowledge benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
CaseLaw (Vals AI)Not measured53.2%Only Qwen3.6 27B measured
CorpFin (Vals AI)Not measured62.3%Only Qwen3.6 27B measured
TaxEval (Vals AI)Not measured71.3%Only Qwen3.6 27B measured
MortgageTax (Vals AI)Not measured68.3%Only Qwen3.6 27B measured
MMLU Pro (Artificial Analysis run)71.4%Not measuredOnly Phi 4 measured
MMLU84.8%Not measuredOnly Phi 4 measured
LMArena Text: science1206Not measuredOnly Phi 4 measured
LMArena Text: medicine and healthcare1202Not measuredOnly Phi 4 measured
LMArena Text: legal and government1241Not measuredOnly Phi 4 measured
LMArena Text: business and finance1199Not measuredOnly Phi 4 measured
Neither model has a result on the other 7 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 27BLeader
SAGE (Vals AI)Not measured45.6%Only Qwen3.6 27B measured
IFBench23.5%67.6%Qwen3.6 27B
Long context reasoning (AA-LCR)0.0%77.3%Qwen3.6 27B
DTBenchNot measured78.1%Only Qwen3.6 27B measured
LMCANot measured34.5%Only Qwen3.6 27B measured
Creative writing (Lech Mazur)62.6%Not measuredOnly Phi 4 measured
LMArena Text1217Not measuredOnly Phi 4 measured
LMArena Text: instruction following1201Not measuredOnly Phi 4 measured
LMArena Text: creative writing1181Not measuredOnly Phi 4 measured
LMArena Text: English1231Not measuredOnly Phi 4 measured
LMArena Text: non-English1197Not measuredOnly Phi 4 measured
LMArena Text: Chinese1212Not measuredOnly Phi 4 measured
LMArena Text: German1222Not measuredOnly Phi 4 measured
LMArena Text: Japanese1158Not measuredOnly Phi 4 measured
LMArena Text: Korean1151Not measuredOnly Phi 4 measured
LMArena Text: French1224Not measuredOnly Phi 4 measured
LMArena Text: Spanish1234Not measuredOnly Phi 4 measured
LMArena Text: Russian1209Not measuredOnly Phi 4 measured
LMArena Text: multi-turn1206Not measuredOnly Phi 4 measured
LMArena Text: longer queries1217Not measuredOnly Phi 4 measured
LMArena Text: writing and language1198Not measuredOnly Phi 4 measured
LMArena Text: entertainment and media1162Not measuredOnly Phi 4 measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Phi 4 and Qwen3.6 27B
BenchmarkPhi 4Qwen3.6 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

Phi 4$0.0001Fits in one request
Qwen3.6 27B$0.0018Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Phi 4$0.0039Exceeds the context window
Qwen3.6 27B$0.031Fits in one request

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Phi 4$0.015Exceeds the context window
Qwen3.6 27B$0.117Fits in one request

Phi 4 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 Phi 4 and Qwen3.6 27B
SpecificationMicrosoft Phi 4Qwen3.6 27B
MakerMicrosoftQwen
WeightsOpen weightsOpen weights
ReleasedJanuary 10, 2025April 27, 2026
Context window16K262K
Input $/Mtok$0.07$0.45
Output $/Mtok$0.14$2.70
Coding indexNot benchmarked36.8
Independent measurements behind it02
Cost per solved taskNot computable$1.30
SourceOpenRouter listingOpenRouter listing

Questions

Is Phi 4 better than Qwen3.6 27B for coding?

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding. Phi 4 has the edge where output tokens cost 19.3x less.

Which is cheaper, Phi 4 or Qwen3.6 27B?

Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.

Which has the bigger context window, Phi 4 or Qwen3.6 27B?

Qwen3.6 27B, with 262K tokens against 16K.

How many benchmarks is the Phi 4 vs Qwen3.6 27B comparison based on?

10 benchmarks have a result for both models as of October 21, 2026. Phi 4's coding index rests on 0 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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