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GLM 4.7 Flash vs Phi 4

Updated October 21, 2026. 35 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.7 Flash Replace Phi 4
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
35
Phi 4Microsoft
Coding
No data
Overall
5.9
Output $/M
$0.14
0
vs boards won of 35 shared

Decision reading

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

GLM 4.7 Flash has the edge where the context window is larger, 200K against 16K tokens.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BPhi 4MicrosoftNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
GLM 4.7 Flash only
8
Phi 4 only
10
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
GLM 4.7 Flash not benchmarked, Phi 4 not benchmarked.
Widest category
Agentic work, 98.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.7 Flash 98.8% against Phi 4 0.0%, 98.8 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against Phi 4 $0.14 per million output tokens, 2.9x apart.
Context window
GLM 4.7 Flash takes 200K 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
CategoryGLM 4.7 FlashBarsPhi 4Ties
Coding30
Intelligence10
Agentic work10
Reasoning60
Math30
Knowledge40
General170
All shared boards350
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
LiveCodeBench (Artificial Analysis run)Not measured23.1%Only Phi 4 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%3.8%GLM 4.7 Flash
LMArena Text: coding13821231GLM 4.7 Flash
LMArena Text: software and IT13891228GLM 4.7 Flash
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 GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
AA Intelligence Index14.95.9GLM 4.7 Flash
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 GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
τ²-Bench Telecom98.8%0.0%GLM 4.7 Flash
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 index60
Reasoning benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
GPQA Diamond (Artificial Analysis run)58.1%57.5%GLM 4.7 Flash
Humanity's Last Exam (Artificial Analysis run)7.6%3.8%GLM 4.7 Flash
GPQA Diamond (Epoch AI run)60.5%56.1%GLM 4.7 Flash
LMArena Text: hard prompts13561220GLM 4.7 Flash
LMArena Text: expert13571203GLM 4.7 Flash
LMArena Text: hard prompts in English13691230GLM 4.7 Flash
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
AA Math IndexNot measured18.0Only Phi 4 measured
AIME 2025 (Artificial Analysis run)Not measured18.0%Only Phi 4 measured
OTIS Mock AIME58.3%13.8%GLM 4.7 Flash
MATH level 5Not measured64.9%Only Phi 4 measured
LMArena Text: math13551246GLM 4.7 Flash
LMArena Text: mathematical work13691254GLM 4.7 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
MMLU Pro (Artificial Analysis run)Not measured71.4%Only Phi 4 measured
MMLUNot measured84.8%Only Phi 4 measured
LMArena Text: science13581206GLM 4.7 Flash
LMArena Text: medicine and healthcare13431202GLM 4.7 Flash
LMArena Text: legal and government13571241GLM 4.7 Flash
LMArena Text: business and finance13431199GLM 4.7 Flash
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
Design Arena: websites1194Not measuredOnly GLM 4.7 Flash measured
Design Arena: UI components1208Not measuredOnly GLM 4.7 Flash measured
Design Arena: game dev1135Not measuredOnly GLM 4.7 Flash measured
Design Arena: data viz1123Not measuredOnly GLM 4.7 Flash measured
Design Arena: 3D1121Not measuredOnly GLM 4.7 Flash measured
Design Arena: all code categories1178Not measuredOnly GLM 4.7 Flash measured
Design Arena: SVG1038Not measuredOnly GLM 4.7 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
General benchmarks for GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 FlashPhi 4Leader
IFBench60.8%23.5%GLM 4.7 Flash
Long context reasoning (AA-LCR)41.7%0.0%GLM 4.7 Flash
Creative writing (Lech Mazur)Not measured62.6%Only Phi 4 measured
LMArena Text13511217GLM 4.7 Flash
LMArena Text: instruction following13271201GLM 4.7 Flash
LMArena Text: creative writing12961181GLM 4.7 Flash
LMArena Text: English13731231GLM 4.7 Flash
LMArena Text: non-English13301197GLM 4.7 Flash
LMArena Text: Chinese14031212GLM 4.7 Flash
LMArena Text: German13361222GLM 4.7 Flash
LMArena Text: JapaneseNot measured1158Only Phi 4 measured
LMArena Text: Korean12831151GLM 4.7 Flash
LMArena Text: French13321224GLM 4.7 Flash
LMArena Text: Spanish13501234GLM 4.7 Flash
LMArena Text: Russian13331209GLM 4.7 Flash
LMArena Text: Polish1291Not measuredOnly GLM 4.7 Flash measured
LMArena Text: multi-turn13421206GLM 4.7 Flash
LMArena Text: longer queries13451217GLM 4.7 Flash
LMArena Text: writing and language13201198GLM 4.7 Flash
LMArena Text: entertainment and media13041162GLM 4.7 Flash
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 GLM 4.7 Flash and Phi 4
BenchmarkGLM 4.7 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

GLM 4.7 Flash$0.0003Fits in one request
Phi 4$0.0001Fits in one request

Phi 4 costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
Phi 4$0.0039Exceeds the context window

Phi 4 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7 Flash$0.017Exceeds the context window
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 GLM 4.7 Flash and Phi 4
SpecificationZ.ai GLM 4.7 FlashMicrosoft Phi 4
MakerZ.aiMicrosoft
WeightsOpen weightsOpen weights
ReleasedJanuary 19, 2026January 10, 2025
Context window200K16K
Input $/Mtok$0.0653$0.07
Output $/Mtok$0.40$0.14
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than Phi 4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where the context window is larger, 200K against 16K tokens.

Which is cheaper, GLM 4.7 Flash or Phi 4?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 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, GLM 4.7 Flash or Phi 4?

GLM 4.7 Flash, with 200K tokens against 16K.

How many benchmarks is the GLM 4.7 Flash vs Phi 4 comparison based on?

35 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 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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