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Gemini 2.5 Flash vs Phi 4

Updated October 21, 2026. 40 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 2.5 Flash Replace Phi 4
Gemini 2.5 FlashGoogle
Coding
No data
Overall
15.5
Output $/M
$2.50
40
Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
0
vs boards won of 40 shared

Decision reading

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

Gemini 2.5 Flash has the edge where the context window is larger, 1.05M against 16K tokens.

Model AGemini 2.5 FlashGoogleNot benchmarkedNo coding benchmark$0.466 per solved taskModel BPhi 4MicrosoftNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
Gemini 2.5 Flash only
29
Phi 4 only
5
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
Gemini 2.5 Flash not benchmarked, Phi 4 not benchmarked.
Widest category
Math, 41.5 points apart on average over 4 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Gemini 2.5 Flash 65.3% against Phi 4 0.0%, 65.3 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash $2.50 against Phi 4 $0.14 per million output tokens, 17.9x apart.
Context window
Gemini 2.5 Flash takes 1.05M 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
CategoryGemini 2.5 FlashBarsPhi 4Ties
Coding40
Intelligence20
Agentic work20
Reasoning50
Math40
Knowledge50
General180
All shared boards400
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
SWE-bench Verified28.7%Not measuredOnly Gemini 2.5 Flash measured
LiveCodeBench (Artificial Analysis run)69.5%23.1%Gemini 2.5 Flash
Terminal-Bench Hard (Artificial Analysis run)13.6%3.8%Gemini 2.5 Flash
Terminal-Bench17.1%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: coding14231231Gemini 2.5 Flash
LMArena Text: software and IT14251228Gemini 2.5 Flash
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
AA Intelligence Index15.55.9Gemini 2.5 Flash
Epoch Capabilities Index142.9130.5Gemini 2.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
τ²-Bench Telecom31.6%0.0%Gemini 2.5 Flash
BALROG33.5%11.6%Gemini 2.5 Flash
Vending-Bench 2$549Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
GPQA Diamond (Artificial Analysis run)79.0%57.5%Gemini 2.5 Flash
Humanity's Last Exam (Artificial Analysis run)12.1%3.8%Gemini 2.5 Flash
GPQA Diamond (Epoch AI run)Not measured56.1%Only Phi 4 measured
ARC-AGI33.3%Not measuredOnly Gemini 2.5 Flash measured
ARC-AGI-22.5%Not measuredOnly Gemini 2.5 Flash measured
SimpleBench41.2%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: hard prompts14221220Gemini 2.5 Flash
LMArena Text: expert14261203Gemini 2.5 Flash
LMArena Text: hard prompts in English14201230Gemini 2.5 Flash
LMArena Vision: diagrams1245Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: homework1244Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
AA Math Index73.318.0Gemini 2.5 Flash
AIME 2025 (Artificial Analysis run)73.3%18.0%Gemini 2.5 Flash
OTIS Mock AIMENot measured13.8%Only Phi 4 measured
MATH level 5Not measured64.9%Only Phi 4 measured
LMArena Text: math14111246Gemini 2.5 Flash
LMArena Text: mathematical work14221254Gemini 2.5 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
MedCode (Vals AI)40.4%Not measuredOnly Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)83.2%71.4%Gemini 2.5 Flash
MMLUNot measured84.8%Only Phi 4 measured
LMArena Text: science14331206Gemini 2.5 Flash
LMArena Text: medicine and healthcare14281202Gemini 2.5 Flash
LMArena Text: legal and government14301241Gemini 2.5 Flash
LMArena Text: business and finance14041199Gemini 2.5 Flash
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
Design Arena: websites1074Not measuredOnly Gemini 2.5 Flash measured
Design Arena: UI components1005Not measuredOnly Gemini 2.5 Flash measured
Design Arena: game dev1005Not measuredOnly Gemini 2.5 Flash measured
Design Arena: data viz1060Not measuredOnly Gemini 2.5 Flash measured
Design Arena: 3D1021Not measuredOnly Gemini 2.5 Flash measured
Design Arena: all code categories1059Not measuredOnly Gemini 2.5 Flash measured
Design Arena: SVG1020Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 4Leader
SAGE (Vals AI)44.8%Not measuredOnly Gemini 2.5 Flash measured
MedScribe (Vals AI)83.0%Not measuredOnly Gemini 2.5 Flash measured
IFBench50.3%23.5%Gemini 2.5 Flash
Long context reasoning (AA-LCR)65.3%0.0%Gemini 2.5 Flash
DTBench76.5%Not measuredOnly Gemini 2.5 Flash measured
LMCA27.5%Not measuredOnly Gemini 2.5 Flash measured
Creative writing (Lech Mazur)Not measured62.6%Only Phi 4 measured
LMArena Text14171217Gemini 2.5 Flash
LMArena Text: instruction following14051201Gemini 2.5 Flash
LMArena Text: creative writing14001181Gemini 2.5 Flash
LMArena Vision1235Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: English14181231Gemini 2.5 Flash
LMArena Text: non-English14091197Gemini 2.5 Flash
LMArena Text: Chinese14491212Gemini 2.5 Flash
LMArena Text: German14171222Gemini 2.5 Flash
LMArena Text: Japanese13961158Gemini 2.5 Flash
LMArena Text: Korean13851151Gemini 2.5 Flash
LMArena Text: French14321224Gemini 2.5 Flash
LMArena Text: Spanish14221234Gemini 2.5 Flash
LMArena Text: Russian14151209Gemini 2.5 Flash
LMArena Text: Polish1413Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: multi-turn14081206Gemini 2.5 Flash
LMArena Text: longer queries14191217Gemini 2.5 Flash
LMArena Text: writing and language14051198Gemini 2.5 Flash
LMArena Text: entertainment and media13931162Gemini 2.5 Flash
LMArena Vision: English1239Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: Chinese1284Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: reading text1237Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: humor1225Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: captioning1277Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: recognizing things1252Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: creative writing1241Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash and Phi 4
BenchmarkGemini 2.5 FlashPhi 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

Gemini 2.5 Flash$0.0015Fits in one request
Phi 4$0.0001Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash$0.022Fits in one request
Phi 4$0.0039Exceeds the context window

Phi 4 costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash$0.085Fits 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 Gemini 2.5 Flash and Phi 4
SpecificationGoogle Gemini 2.5 FlashMicrosoft Phi 4
MakerGoogleMicrosoft
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025January 10, 2025
Context window1.05M16K
Input $/Mtok$0.30$0.07
Output $/Mtok$2.50$0.14
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$0.466Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash better than Phi 4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Gemini 2.5 Flash has the edge where the context window is larger, 1.05M against 16K tokens.

Which is cheaper, Gemini 2.5 Flash or Phi 4?

Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; Phi 4 costs $0.07 and $0.14. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, Gemini 2.5 Flash or Phi 4?

Gemini 2.5 Flash, with 1.05M tokens against 16K.

How many benchmarks is the Gemini 2.5 Flash vs Phi 4 comparison based on?

40 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash'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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