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Phi 4 vs Qwen3.5-Flash

Phi 4 costs 1.9x less per output token than Qwen3.5-Flash ($0.14 vs $0.26 per million). Updated October 21, 2026; 30 benchmarks have a result for both.

Replace Phi 4 Replace Qwen3.5-Flash
Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
0
Qwen3.5-FlashQwen
Coding
41.1
Overall
No data
Output $/M
$0.26
30
vs boards won of 30 shared

Phi 4 or Qwen3.5-Flash: which to pick

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding.

Pick Phi 4 for output tokens 1.9x cheaper ($0.14 vs $0.26 per million).

Model APhi 4MicrosoftNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
30
Phi 4 only
15
Qwen3.5-Flash only
25
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
Phi 4 not benchmarked, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
Math, 41.4 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: Phi 4 13.8% against Qwen3.5-Flash 84.4%, 70.7 points apart on a 0 to 100 scale.
Output price
Phi 4 $0.14 against Qwen3.5-Flash $0.26 per million output tokens, 1.9x apart.
Context window
Phi 4 takes 16K tokens, Qwen3.5-Flash 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
CategoryPhi 4BarsQwen3.5-FlashTies
Coding02
Intelligence01
Reasoning04
Math03
Knowledge04
General016
All shared boards030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
LiveCodeBench (Artificial Analysis run)23.1%Not measuredOnly Phi 4 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly Phi 4 measured
ALE-BenchNot measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding12311412Qwen3.5-Flash
LMArena Text: software and IT12281416Qwen3.5-Flash
LMArena WebDev: ReactNot measured1229Only Qwen3.5-Flash measured
LMArena WebDev: HTMLNot measured1291Only Qwen3.5-Flash measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
AA Intelligence Index5.9Not measuredOnly Phi 4 measured
Epoch Capabilities Index130.5143.5Qwen3.5-Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
τ²-Bench Telecom0.0%Not measuredOnly Phi 4 measured
BALROG11.6%Not measuredOnly Phi 4 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)57.5%Not measuredOnly Phi 4 measured
Humanity's Last Exam (Artificial Analysis run)3.8%Not measuredOnly Phi 4 measured
GPQA Diamond (Epoch AI run)56.1%82.3%Qwen3.5-Flash
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts12201403Qwen3.5-Flash
LMArena Text: expert12031407Qwen3.5-Flash
LMArena Text: hard prompts in English12301409Qwen3.5-Flash
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
AA Math Index18.0Not measuredOnly Phi 4 measured
AIME 2025 (Artificial Analysis run)18.0%Not measuredOnly Phi 4 measured
OTIS Mock AIME13.8%84.4%Qwen3.5-Flash
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
MATH level 564.9%Not measuredOnly Phi 4 measured
LMArena Text: math12461407Qwen3.5-Flash
LMArena Text: mathematical work12541413Qwen3.5-Flash
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
MMLU Pro (Artificial Analysis run)71.4%Not measuredOnly Phi 4 measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
MMLU84.8%Not measuredOnly Phi 4 measured
LMArena Text: science12061415Qwen3.5-Flash
LMArena Text: medicine and healthcare12021407Qwen3.5-Flash
LMArena Text: legal and government12411398Qwen3.5-Flash
LMArena Text: business and finance11991394Qwen3.5-Flash
Neither model has a result on the other 3 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
IFBench23.5%Not measuredOnly Phi 4 measured
Long context reasoning (AA-LCR)0.0%Not measuredOnly Phi 4 measured
DTBenchNot measured82.9%Only Qwen3.5-Flash measured
LMCANot measured29.1%Only Qwen3.5-Flash measured
Creative writing (Lech Mazur)62.6%Not measuredOnly Phi 4 measured
LMArena Text12171397Qwen3.5-Flash
LMArena Text: instruction following12011374Qwen3.5-Flash
LMArena Text: creative writing11811343Qwen3.5-Flash
LMArena Text: English12311404Qwen3.5-Flash
LMArena Text: non-English11971385Qwen3.5-Flash
LMArena Text: Chinese12121445Qwen3.5-Flash
LMArena Text: German12221390Qwen3.5-Flash
LMArena Text: Japanese11581369Qwen3.5-Flash
LMArena Text: Korean11511344Qwen3.5-Flash
LMArena Text: French12241413Qwen3.5-Flash
LMArena Text: Spanish12341400Qwen3.5-Flash
LMArena Text: Russian12091380Qwen3.5-Flash
LMArena Text: PolishNot measured1376Only Qwen3.5-Flash measured
LMArena Text: multi-turn12061393Qwen3.5-Flash
LMArena Text: longer queries12171392Qwen3.5-Flash
LMArena Text: writing and language11981369Qwen3.5-Flash
LMArena Text: entertainment and media11621347Qwen3.5-Flash
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Phi 4 and Qwen3.5-Flash
BenchmarkPhi 4Qwen3.5-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

Phi 4$0.0001Fits in one request
Qwen3.5-Flash$0.0002Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Phi 4$0.0039Exceeds the context window
Qwen3.5-Flash$0.0040Fits in one request

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Phi 4$0.015Exceeds the context window
Qwen3.5-Flash$0.016Fits 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 Qwen3.5-Flash
SpecificationMicrosoft Phi 4Qwen3.5-Flash
MakerMicrosoftQwen
WeightsOpen weightsNo public weights listed
ReleasedJanuary 10, 2025February 25, 2026
Context window16K1M
Input $/Mtok$0.07$0.065
Output $/Mtok$0.14$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it02
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is Phi 4 better than Qwen3.5-Flash for coding?

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding. Pick Phi 4 for output tokens 1.9x cheaper ($0.14 vs $0.26 per million).

Which is cheaper, Phi 4 or Qwen3.5-Flash?

Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

Which has the bigger context window, Phi 4 or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 16K.

How many benchmarks is the Phi 4 vs Qwen3.5-Flash comparison based on?

30 benchmarks have a result for both models as of October 21, 2026. Phi 4's coding index rests on 0 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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