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Phi 4 vs Qwen3.6 35B A3B

Qwen3.6 35B A3B leads Phi 4 on the Artificial Analysis Intelligence Index, 18.2 to 5.9, and Phi 4 costs 7.1x less per output token ($0.14 vs $1.00 per million). Updated October 21, 2026; 10 benchmarks have a result for both.

Phi 4Microsoft
Coding
No data
Overall
24.7
Output $/M
$0.14
0
Qwen3.6 35B A3BQwen
Coding
No data
Overall
45.0
Output $/M
$1.00
10
vs boards won of 10 shared

Phi 4 or Qwen3.6 35B A3B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Phi 4 for output tokens 7.1x cheaper ($0.14 vs $1.00 per million) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Shared results
10
Phi 4 only
36
Qwen3.6 35B A3B only
10
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, Qwen3.6 35B A3B not benchmarked.
Widest category
Agentic work, 95.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Phi 4 0.0% against Qwen3.6 35B A3B 95.3%, 95.3 points apart on a 0 to 100 scale.
Output price
Phi 4 $0.14 against Qwen3.6 35B A3B $1.00 per million output tokens, 7.1x apart.
Context window
Phi 4 takes 16K tokens, Qwen3.6 35B A3B 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 35B A3BTies
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 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
AA Coding IndexNot measured41.9Only Qwen3.6 35B A3B measured
LiveCodeBench (Artificial Analysis run)23.1%Not measuredOnly Phi 4 measured
SciCodeNot measured36.6%Only Qwen3.6 35B A3B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%34.8%Qwen3.6 35B A3B
Terminal-BenchNot measured24.6%Only Qwen3.6 35B A3B measured
WeirdMLNot measured34.5%Only Qwen3.6 35B A3B measured
LMArena Text: coding1231Not measuredOnly Phi 4 measured
LMArena Text: software and IT1228Not measuredOnly Phi 4 measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Phi 4 and Qwen3.6 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
AA Intelligence Index5.918.2Qwen3.6 35B A3B
Epoch Capabilities Index130.5143.7Qwen3.6 35B A3B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Phi 4 and Qwen3.6 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
AA Agentic IndexNot measured13.1Only Qwen3.6 35B A3B measured
τ²-Bench Telecom0.0%95.3%Qwen3.6 35B A3B
BALROG11.6%Not measuredOnly Phi 4 measured
Berkeley Function Calling Leaderboard (BFCL)28.8%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 index03
Reasoning benchmarks for Phi 4 and Qwen3.6 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
GPQA Diamond (Artificial Analysis run)57.5%84.1%Qwen3.6 35B A3B
Humanity's Last Exam (Artificial Analysis run)3.8%22.2%Qwen3.6 35B A3B
GPQA Diamond (Epoch AI run)56.1%84.8%Qwen3.6 35B A3B
Mystery game puzzlesNot measured22.0%Only Qwen3.6 35B A3B 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 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for Phi 4 and Qwen3.6 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
AA Math Index18.0Not measuredOnly Phi 4 measured
AIME 2025 (Artificial Analysis run)18.0%Not measuredOnly Phi 4 measured
OTIS Mock AIME13.8%86.7%Qwen3.6 35B A3B
FrontierMath, tiers 1 to 3Not measured20.4%Only Qwen3.6 35B A3B 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 index6 boards, none shared
Knowledge benchmarks for Phi 4 and Qwen3.6 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
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 12 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 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
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 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
IFBench23.5%64.4%Qwen3.6 35B A3B
Long context reasoning (AA-LCR)0.0%71.7%Qwen3.6 35B A3B
DTBenchNot measured73.9%Only Qwen3.6 35B A3B measured
LMCANot measured29.7%Only Qwen3.6 35B A3B measured
Creative writing (Lech Mazur)62.6%Not measuredOnly Phi 4 measured
Surface Evolver BenchNot measured44.4%Only Qwen3.6 35B A3B 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 35B A3B
BenchmarkPhi 4Qwen3.6 35B A3BLeader
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 35B A3B$0.0006Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Phi 4$0.0039Exceeds the context window
Qwen3.6 35B A3B$0.0080Fits in one request

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Phi 4$0.015Exceeds the context window
Qwen3.6 35B A3B$0.030Fits 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 35B A3B
SpecificationMicrosoft Phi 4Qwen3.6 35B A3B
MakerMicrosoftQwen
WeightsOpen weightsOpen weights
ReleasedJanuary 10, 2025April 27, 2026
Context window16K262K
Input $/Mtok$0.07$0.10
Output $/Mtok$0.14$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Phi 4 better than Qwen3.6 35B A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Phi 4 for output tokens 7.1x cheaper ($0.14 vs $1.00 per million) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, Phi 4 or Qwen3.6 35B A3B?

Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Phi 4 or Qwen3.6 35B A3B?

Qwen3.6 35B A3B, with 262K tokens against 16K.

How many benchmarks is the Phi 4 vs Qwen3.6 35B A3B 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 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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