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DeepSeek V4 Flash 0423 vs GLM 4.7 Flash

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 DeepSeek V4 Flash 0423 Replace GLM 4.7 Flash
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
24.4
Output $/M
$0.28
34
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
1
vs boards won of 35 shared

Decision reading

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

DeepSeek V4 Flash 0423 has the edge where output tokens cost 1.4x less, and where the context window is larger, 1.05M against 200K tokens.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
DeepSeek V4 Flash 0423 only
13
GLM 4.7 Flash only
8
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
DeepSeek V4 Flash 0423 not benchmarked, GLM 4.7 Flash not benchmarked.
Widest category
General, 15.6 points apart on average over 16 shared benchmarks.
Widest single gap
LMArena Text: Polish: DeepSeek V4 Flash 0423 1436 against GLM 4.7 Flash 1291, 24.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GLM 4.7 Flash $0.40 per million output tokens, 1.4x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GLM 4.7 Flash 200K.

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
CategoryDeepSeek V4 Flash 0423BarsGLM 4.7 FlashTies
Coding20
Intelligence10
Reasoning30
Math20
Knowledge40
Web design61
General160
All shared boards341
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured22.0%Only GLM 4.7 Flash measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571382DeepSeek V4 Flash 0423
LMArena Text: software and IT14531389DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
AA Intelligence Index24.414.9DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured98.8%Only GLM 4.7 Flash measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
GPQA Diamond (Artificial Analysis run)Not measured58.1%Only GLM 4.7 Flash measured
Humanity's Last Exam (Artificial Analysis run)Not measured7.6%Only GLM 4.7 Flash measured
GPQA Diamond (Epoch AI run)Not measured60.5%Only GLM 4.7 Flash measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441356DeepSeek V4 Flash 0423
LMArena Text: expert14411357DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491369DeepSeek V4 Flash 0423
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
OTIS Mock AIMENot measured58.3%Only GLM 4.7 Flash measured
LMArena Text: math14261355DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321369DeepSeek V4 Flash 0423
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
LMArena Text: science14461358DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481343DeepSeek V4 Flash 0423
LMArena Text: legal and government14391357DeepSeek V4 Flash 0423
LMArena Text: business and finance14251343DeepSeek V4 Flash 0423
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
Design Arena: websites12081194DeepSeek V4 Flash 0423
Design Arena: UI components11651208GLM 4.7 Flash
Design Arena: game dev11971135DeepSeek V4 Flash 0423
Design Arena: data viz11271123DeepSeek V4 Flash 0423
Design Arena: 3D11891121DeepSeek V4 Flash 0423
Design Arena: all code categories12051178DeepSeek V4 Flash 0423
Design Arena: SVG11551038DeepSeek V4 Flash 0423
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
General benchmarks for DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
IFBenchNot measured60.8%Only GLM 4.7 Flash measured
Long context reasoning (AA-LCR)Not measured41.7%Only GLM 4.7 Flash measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321351DeepSeek V4 Flash 0423
LMArena Text: instruction following14211327DeepSeek V4 Flash 0423
LMArena Text: creative writing14031296DeepSeek V4 Flash 0423
LMArena Text: English14411373DeepSeek V4 Flash 0423
LMArena Text: non-English14191330DeepSeek V4 Flash 0423
LMArena Text: Chinese14631403DeepSeek V4 Flash 0423
LMArena Text: German14191336DeepSeek V4 Flash 0423
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean13831283DeepSeek V4 Flash 0423
LMArena Text: French14391332DeepSeek V4 Flash 0423
LMArena Text: Spanish14361350DeepSeek V4 Flash 0423
LMArena Text: Russian14271333DeepSeek V4 Flash 0423
LMArena Text: Polish14361291DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491342DeepSeek V4 Flash 0423
LMArena Text: longer queries14341345DeepSeek V4 Flash 0423
LMArena Text: writing and language14101320DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001304DeepSeek V4 Flash 0423
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 DeepSeek V4 Flash 0423 and GLM 4.7 Flash
BenchmarkDeepSeek V4 Flash 0423GLM 4.7 FlashLeader
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

DeepSeek V4 Flash 0423$0.0003Fits in one request
GLM 4.7 Flash$0.0003Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
GLM 4.7 Flash$0.0045Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
GLM 4.7 Flash$0.017Exceeds the context window

GLM 4.7 Flash 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 DeepSeek V4 Flash 0423 and GLM 4.7 Flash
SpecificationDeepSeek V4 Flash 0423Z.ai GLM 4.7 Flash
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026January 19, 2026
Context window1.05M200K
Input $/Mtok$0.14$0.0653
Output $/Mtok$0.28$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GLM 4.7 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. DeepSeek V4 Flash 0423 has the edge where output tokens cost 1.4x less, and where the context window is larger, 1.05M against 200K tokens.

Which is cheaper, DeepSeek V4 Flash 0423 or GLM 4.7 Flash?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GLM 4.7 Flash?

DeepSeek V4 Flash 0423, with 1.05M tokens against 200K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs GLM 4.7 Flash comparison based on?

35 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and GLM 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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