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Nova Lite 1.0 vs Phi 4

Nova Lite 1.0 leads Phi 4 on the Artificial Analysis Intelligence Index, 6.7 to 5.9, and Phi 4 costs 1.7x less per output token ($0.14 vs $0.24 per million). Updated October 21, 2026; 39 benchmarks have a result for both.

Nova Lite 1.0Amazon
Coding
No data
Overall
6.7
Output $/M
$0.24
24
Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
15
vs boards won of 39 shared

Nova Lite 1.0 or Phi 4: which to pick

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

Pick Nova Lite 1.0 for a larger context window (300K against 16K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Shared results
39
Nova Lite 1.0 only
2
Phi 4 only
6
Like-for-like categories
7 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
Nova Lite 1.0 not benchmarked, Phi 4 not benchmarked.
Widest category
Agentic work, 17.5 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): Nova Lite 1.0 19.0% against Phi 4 0.0%, 19.0 points apart on a 0 to 100 scale.
Output price
Nova Lite 1.0 $0.24 against Phi 4 $0.14 per million output tokens, 1.7x apart.
Context window
Nova Lite 1.0 takes 300K tokens, Phi 4 16K.

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
CategoryNova Lite 1.0BarsPhi 4Ties
Coding22
Intelligence10
Agentic work10
Reasoning23
Math04
Knowledge33
General153
All shared boards2415
CodingLike-for-likeSix of these boards feed the Vibe Coding Index22
Coding benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
LiveCodeBench (Artificial Analysis run)16.7%23.1%Phi 4
Terminal-Bench Hard (Artificial Analysis run)0.8%3.8%Phi 4
LMArena Text: coding12391231Nova Lite 1.0
LMArena Text: software and IT12411228Nova Lite 1.0
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
AA Intelligence Index6.75.9Nova Lite 1.0
Epoch Capabilities IndexNot measured130.5Only Phi 4 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
τ²-Bench Telecom17.5%0.0%Nova Lite 1.0
BALROGNot measured11.6%Only 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 index23
Reasoning benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
GPQA Diamond (Artificial Analysis run)43.3%57.5%Phi 4
Humanity's Last Exam (Artificial Analysis run)4.3%3.8%Nova Lite 1.0
GPQA Diamond (Epoch AI run)Not measured56.1%Only Phi 4 measured
LMArena Text: hard prompts12201220Nova Lite 1.0
LMArena Text: expert12011203Phi 4
LMArena Text: hard prompts in English12261230Phi 4
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
AA Math Index7.018.0Phi 4
AIME 2025 (Artificial Analysis run)7.0%18.0%Phi 4
OTIS Mock AIMENot measured13.8%Only Phi 4 measured
MATH level 5Not measured64.9%Only Phi 4 measured
LMArena Text: math12271246Phi 4
LMArena Text: mathematical work12351254Phi 4
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
Knowledge benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
MMLU Pro (Artificial Analysis run)59.0%71.4%Phi 4
MMLU77.0%84.8%Phi 4
LMArena Text: science12321206Nova Lite 1.0
LMArena Text: medicine and healthcare12131202Nova Lite 1.0
LMArena Text: legal and government12381241Phi 4
LMArena Text: business and finance12191199Nova Lite 1.0
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index153
General benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
IFBench34.1%23.5%Nova Lite 1.0
Long context reasoning (AA-LCR)19.0%0.0%Nova Lite 1.0
Creative writing (Lech Mazur)Not measured62.6%Only Phi 4 measured
LMArena Text12291217Nova Lite 1.0
LMArena Text: instruction following12051201Nova Lite 1.0
LMArena Text: creative writing11971181Nova Lite 1.0
LMArena Vision990Not measuredOnly Nova Lite 1.0 measured
LMArena Text: English12431231Nova Lite 1.0
LMArena Text: non-English12081197Nova Lite 1.0
LMArena Text: Chinese12251212Nova Lite 1.0
LMArena Text: German12291222Nova Lite 1.0
LMArena Text: Japanese11531158Phi 4
LMArena Text: Korean11531151Nova Lite 1.0
LMArena Text: French12381224Nova Lite 1.0
LMArena Text: Spanish12261234Phi 4
LMArena Text: Russian12161209Nova Lite 1.0
LMArena Text: multi-turn11991206Phi 4
LMArena Text: longer queries12341217Nova Lite 1.0
LMArena Text: writing and language12111198Nova Lite 1.0
LMArena Text: entertainment and media11761162Nova Lite 1.0
LMArena Vision: English999Not measuredOnly Nova Lite 1.0 measured
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Nova Lite 1.0 and Phi 4
BenchmarkNova Lite 1.0Phi 4Leader
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

Nova Lite 1.0$0.0002Fits in one request
Phi 4$0.0001Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Nova Lite 1.0$0.0037Fits in one request
Phi 4$0.0039Exceeds the context window

Nova Lite 1.0 costs less

Agent loop

200K input + 10K output tokens

Nova Lite 1.0$0.014Fits in one request
Phi 4$0.015Exceeds the context window

Nova Lite 1.0 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 Nova Lite 1.0 and Phi 4
SpecificationAmazon Nova Lite 1.0Microsoft Phi 4
MakerAmazonMicrosoft
WeightsNo public weights listedOpen weights
ReleasedDecember 5, 2024January 10, 2025
Context window300K16K
Input $/Mtok$0.06$0.07
Output $/Mtok$0.24$0.14
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nova Lite 1.0 better than Phi 4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Lite 1.0 for a larger context window (300K against 16K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Nova Lite 1.0 or Phi 4?

Nova Lite 1.0 costs $0.06 per million input tokens and $0.24 per million output tokens; Phi 4 costs $0.07 and $0.14. Cost per solved task is known for neither of them.

Which has the bigger context window, Nova Lite 1.0 or Phi 4?

Nova Lite 1.0, with 300K tokens against 16K.

How many benchmarks is the Nova Lite 1.0 vs Phi 4 comparison based on?

39 benchmarks have a result for both models as of October 21, 2026. Nova Lite 1.0's coding index rests on 0 independent benchmarks and Phi 4's on 0. Where only one model has a result, the page says so instead of naming a winner.

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