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Phi 4 vs Hy3

Updated October 21, 2026. 30 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
Hy3Tencent
Coding
No data
Overall
No data
Output $/M
$0.528
30
vs boards won of 30 shared

Decision reading

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

Phi 4 has the edge where output tokens cost 3.8x less, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
30
Phi 4 only
15
Hy3 only
14
Like-for-like categories
5 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, Hy3 not benchmarked.
Widest category
General, 40.8 points apart on average over 17 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Phi 4 0.0% against Hy3 79.0%, 79.0 points apart on a 0 to 100 scale.
Output price
Phi 4 $0.14 against Hy3 $0.528 per million output tokens, 3.8x apart.
Context window
Phi 4 takes 16K tokens, Hy3 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 4BarsHy3Ties
Coding02
Reasoning05
Math02
Knowledge04
General017
All shared boards030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
LMArena WebDevNot measured1507Only Hy3 measured
LiveCodeBench (Artificial Analysis run)23.1%Not measuredOnly Phi 4 measured
SciCodeNot measured48.6%Only Hy3 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly Phi 4 measured
ALE-BenchNot measured838.6Only Hy3 measured
LMArena Text: coding12311466Hy3
LMArena Text: software and IT12281463Hy3
LMArena WebDev: ReactNot measured1511Only Hy3 measured
LMArena WebDev: HTMLNot measured1487Only Hy3 measured
Neither model has a result on the other 29 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
AA Intelligence Index5.9Not measuredOnly Phi 4 measured
Epoch Capabilities Index130.5Not measuredOnly Phi 4 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
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 index05
Reasoning benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
GPQA Diamond (Artificial Analysis run)57.5%89.7%Hy3
Humanity's Last Exam (Artificial Analysis run)3.8%33.5%Hy3
GPQA Diamond (Epoch AI run)56.1%Not measuredOnly Phi 4 measured
LMArena Text: hard prompts12201447Hy3
LMArena Text: expert12031461Hy3
LMArena Text: hard prompts in English12301455Hy3
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
AA Math Index18.0Not measuredOnly Phi 4 measured
AIME 2025 (Artificial Analysis run)18.0%Not measuredOnly Phi 4 measured
OTIS Mock AIME13.8%Not measuredOnly Phi 4 measured
MATH level 564.9%Not measuredOnly Phi 4 measured
LMArena Text: math12461473Hy3
LMArena Text: mathematical work12541482Hy3
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
MMLU Pro (Artificial Analysis run)71.4%Not measuredOnly Phi 4 measured
MMLU84.8%Not measuredOnly Phi 4 measured
LMArena Text: science12061457Hy3
LMArena Text: medicine and healthcare12021452Hy3
LMArena Text: legal and government12411422Hy3
LMArena Text: business and finance11991424Hy3
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
Design Arena: websitesNot measured1230Only Hy3 measured
Design Arena: UI componentsNot measured1207Only Hy3 measured
Design Arena: game devNot measured1208Only Hy3 measured
Design Arena: data vizNot measured1163Only Hy3 measured
Design Arena: 3DNot measured1233Only Hy3 measured
Design Arena: all code categoriesNot measured1227Only Hy3 measured
Design Arena: SVGNot measured1200Only Hy3 measured
Design Arena: ASCII artNot measured1157Only Hy3 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
IFBench23.5%Not measuredOnly Phi 4 measured
Long context reasoning (AA-LCR)0.0%79.0%Hy3
Creative writing (Lech Mazur)62.6%Not measuredOnly Phi 4 measured
LMArena Text12171438Hy3
LMArena Text: instruction following12011426Hy3
LMArena Text: creative writing11811403Hy3
LMArena Text: English12311448Hy3
LMArena Text: non-English11971426Hy3
LMArena Text: Chinese12121485Hy3
LMArena Text: German12221449Hy3
LMArena Text: Japanese11581397Hy3
LMArena Text: Korean11511396Hy3
LMArena Text: French12241456Hy3
LMArena Text: Spanish12341457Hy3
LMArena Text: Russian12091432Hy3
LMArena Text: PolishNot measured1447Only Hy3 measured
LMArena Text: multi-turn12061436Hy3
LMArena Text: longer queries12171442Hy3
LMArena Text: writing and language11981414Hy3
LMArena Text: entertainment and media11621400Hy3
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Phi 4 and Hy3
BenchmarkPhi 4Hy3Leader
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
Hy3$0.0004Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Phi 4$0.0039Exceeds the context window
Hy3$0.0082Fits in one request

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Phi 4$0.015Exceeds the context window
Hy3$0.032Fits 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 Hy3
SpecificationMicrosoft Phi 4Tencent Hy3
MakerMicrosoftTencent
WeightsOpen weightsOpen weights
ReleasedJanuary 10, 2025July 6, 2026
Context window16K262K
Input $/Mtok$0.07$0.132
Output $/Mtok$0.14$0.528
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Phi 4 better than Hy3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Phi 4 has the edge where output tokens cost 3.8x less, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Phi 4 or Hy3?

Phi 4 costs $0.07 per million input tokens and $0.14 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for neither of them.

Which has the bigger context window, Phi 4 or Hy3?

Hy3, with 262K tokens against 16K.

How many benchmarks is the Phi 4 vs Hy3 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 Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.

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