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Nova Pro 1.0 vs Phi 4

Updated October 21, 2026. 39 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Nova Pro 1.0Amazon
Coding
No data
Overall
7.0
Output $/M
$3.20
32
Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
7
vs boards won of 39 shared

Decision reading

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

Nova Pro 1.0 has the edge where the context window is larger, 300K against 16K tokens, and where what matters is GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Shared results
39
Nova Pro 1.0 only
3
Phi 4 only
6
Like-for-like categories
7 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
Nova Pro 1.0 not benchmarked, Phi 4 not benchmarked.
Widest category
Agentic work, 14.0 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): Nova Pro 1.0 21.0% against Phi 4 0.0%, 21.0 points apart on a 0 to 100 scale.
Output price
Nova Pro 1.0 $3.20 against Phi 4 $0.14 per million output tokens, 22.9x apart.
Context window
Nova Pro 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 Pro 1.0BarsPhi 4Ties
Coding40
Intelligence10
Agentic work10
Reasoning32
Math22
Knowledge42
General171
All shared boards327
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
LiveCodeBench (Artificial Analysis run)23.3%23.1%Nova Pro 1.0
Terminal-Bench Hard (Artificial Analysis run)6.1%3.8%Nova Pro 1.0
LMArena Text: coding12701231Nova Pro 1.0
LMArena Text: software and IT12711228Nova Pro 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 Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
AA Intelligence Index7.05.9Nova Pro 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 Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
τ²-Bench Telecom14.0%0.0%Nova Pro 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 index32
Reasoning benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
GPQA Diamond (Artificial Analysis run)49.9%57.5%Phi 4
Humanity's Last Exam (Artificial Analysis run)3.2%3.8%Phi 4
GPQA Diamond (Epoch AI run)Not measured56.1%Only Phi 4 measured
LMArena Text: hard prompts12461220Nova Pro 1.0
LMArena Text: expert12111203Nova Pro 1.0
LMArena Text: hard prompts in English12591230Nova Pro 1.0
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 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: math12521246Nova Pro 1.0
LMArena Text: mathematical work12611254Nova Pro 1.0
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index42
Knowledge benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
MMLU Pro (Artificial Analysis run)69.1%71.4%Phi 4
MMLU82.0%84.8%Phi 4
LMArena Text: science12551206Nova Pro 1.0
LMArena Text: medicine and healthcare12601202Nova Pro 1.0
LMArena Text: legal and government12811241Nova Pro 1.0
LMArena Text: business and finance12291199Nova Pro 1.0
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
Design Arena: websites796Not measuredOnly Nova Pro 1.0 measured
Neither model has a result on the other 8 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
General benchmarks for Nova Pro 1.0 and Phi 4
BenchmarkNova Pro 1.0Phi 4Leader
IFBench38.1%23.5%Nova Pro 1.0
Long context reasoning (AA-LCR)21.0%0.0%Nova Pro 1.0
Creative writing (Lech Mazur)Not measured62.6%Only Phi 4 measured
LMArena Text12591217Nova Pro 1.0
LMArena Text: instruction following12351201Nova Pro 1.0
LMArena Text: creative writing12121181Nova Pro 1.0
LMArena Vision980Not measuredOnly Nova Pro 1.0 measured
LMArena Text: English12761231Nova Pro 1.0
LMArena Text: non-English12331197Nova Pro 1.0
LMArena Text: Chinese12441212Nova Pro 1.0
LMArena Text: German12431222Nova Pro 1.0
LMArena Text: Japanese12001158Nova Pro 1.0
LMArena Text: Korean12031151Nova Pro 1.0
LMArena Text: French12711224Nova Pro 1.0
LMArena Text: Spanish11821234Phi 4
LMArena Text: Russian12401209Nova Pro 1.0
LMArena Text: multi-turn12461206Nova Pro 1.0
LMArena Text: longer queries12551217Nova Pro 1.0
LMArena Text: writing and language12471198Nova Pro 1.0
LMArena Text: entertainment and media12101162Nova Pro 1.0
LMArena Vision: English987Not measuredOnly Nova Pro 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 Pro 1.0 and Phi 4
BenchmarkNova Pro 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 Pro 1.0$0.0024Fits in one request
Phi 4$0.0001Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Nova Pro 1.0$0.050Fits in one request
Phi 4$0.0039Exceeds the context window

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Nova Pro 1.0$0.192Fits in one request
Phi 4$0.015Exceeds the context window

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 Nova Pro 1.0 and Phi 4
SpecificationAmazon Nova Pro 1.0Microsoft Phi 4
MakerAmazonMicrosoft
WeightsNo public weights listedOpen weights
ReleasedDecember 5, 2024January 10, 2025
Context window300K16K
Input $/Mtok$0.80$0.07
Output $/Mtok$3.20$0.14
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nova Pro 1.0 better than Phi 4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Nova Pro 1.0 has the edge where the context window is larger, 300K against 16K tokens, and where what matters is GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, Nova Pro 1.0 or Phi 4?

Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 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 Pro 1.0 or Phi 4?

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

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

39 benchmarks have a result for both models as of October 21, 2026. Nova Pro 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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