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DeepSeek V4 Flash 0423 vs GLM 4.5 Air

DeepSeek V4 Flash 0423 leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 24.4 to 11.1, and DeepSeek V4 Flash 0423 costs 3.9x less per output token ($0.28 vs $1.10 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
36
GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
1
vs boards won of 37 shared

DeepSeek V4 Flash 0423 or GLM 4.5 Air: which to pick

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

Pick DeepSeek V4 Flash 0423 for output tokens 3.9x cheaper ($0.28 vs $1.10 per million) and a larger context window (1.05M against 131K tokens).

Shared results
37
DeepSeek V4 Flash 0423 only
12
GLM 4.5 Air only
11
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
DeepSeek V4 Flash 0423 not benchmarked, GLM 4.5 Air not benchmarked.
Widest category
Intelligence, 13.3 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: DeepSeek V4 Flash 0423 24.4 against GLM 4.5 Air 11.1, 13.3 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GLM 4.5 Air $1.10 per million output tokens, 3.9x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GLM 4.5 Air 131K.

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 4.5 AirTies
Coding20
Intelligence10
Reasoning40
Math20
Knowledge40
Web design61
General170
All shared boards361
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Artificial Analysis run)Not measured68.4%Only GLM 4.5 Air measured
Terminal-Bench Hard (Artificial Analysis run)Not measured20.5%Only GLM 4.5 Air measured
GSO-BenchNot measured2.9%Only GLM 4.5 Air measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571397DeepSeek V4 Flash 0423
LMArena Text: software and IT14531401DeepSeek 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 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
AA Intelligence Index24.411.1DeepSeek 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 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured46.5%Only GLM 4.5 Air measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
GPQA Diamond (Artificial Analysis run)Not measured73.3%Only GLM 4.5 Air measured
Humanity's Last Exam (Artificial Analysis run)Not measured7.0%Only GLM 4.5 Air measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441379DeepSeek V4 Flash 0423
LMArena Text: expert14411370DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491388DeepSeek V4 Flash 0423
Kagi LLM Benchmark52.2%43.0%DeepSeek V4 Flash 0423
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
AA Math IndexNot measured80.7Only GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)Not measured80.7%Only GLM 4.5 Air measured
LMArena Text: math14261396DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321396DeepSeek V4 Flash 0423
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
MMLU Pro (Artificial Analysis run)Not measured81.5%Only GLM 4.5 Air measured
LMArena Text: science14461407DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481402DeepSeek V4 Flash 0423
LMArena Text: legal and government14391382DeepSeek V4 Flash 0423
LMArena Text: business and finance14251371DeepSeek 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 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
Design Arena: websites12071146DeepSeek V4 Flash 0423
Design Arena: UI components11621120DeepSeek V4 Flash 0423
Design Arena: game dev11961094DeepSeek V4 Flash 0423
Design Arena: data viz11271186GLM 4.5 Air
Design Arena: 3D11881122DeepSeek V4 Flash 0423
Design Arena: all code categories12051137DeepSeek V4 Flash 0423
Design Arena: SVG11551071DeepSeek 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 index170
General benchmarks for DeepSeek V4 Flash 0423 and GLM 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
IFBenchNot measured37.6%Only GLM 4.5 Air measured
Long context reasoning (AA-LCR)Not measured46.7%Only GLM 4.5 Air measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321384DeepSeek V4 Flash 0423
LMArena Text: instruction following14211354DeepSeek V4 Flash 0423
LMArena Text: creative writing14031343DeepSeek V4 Flash 0423
LMArena Text: English14411397DeepSeek V4 Flash 0423
LMArena Text: non-English14191366DeepSeek V4 Flash 0423
LMArena Text: Chinese14631426DeepSeek V4 Flash 0423
LMArena Text: German14191377DeepSeek V4 Flash 0423
LMArena Text: Japanese13891348DeepSeek V4 Flash 0423
LMArena Text: Korean13831308DeepSeek V4 Flash 0423
LMArena Text: French14391400DeepSeek V4 Flash 0423
LMArena Text: Spanish14361385DeepSeek V4 Flash 0423
LMArena Text: Russian14271373DeepSeek V4 Flash 0423
LMArena Text: Polish14361368DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491371DeepSeek V4 Flash 0423
LMArena Text: longer queries14341366DeepSeek V4 Flash 0423
LMArena Text: writing and language14101354DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001339DeepSeek 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 4.5 Air
BenchmarkDeepSeek V4 Flash 0423GLM 4.5 AirLeader
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 4.5 Air$0.0008Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
GLM 4.5 Air$0.013Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
GLM 4.5 Air$0.051Exceeds the context window

DeepSeek V4 Flash 0423 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 4.5 Air
SpecificationDeepSeek V4 Flash 0423Z.ai GLM 4.5 Air
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026July 25, 2025
Context window1.05M131K
Input $/Mtok$0.14$0.20
Output $/Mtok$0.28$1.10
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 4.5 Air for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 3.9x cheaper ($0.28 vs $1.10 per million) and a larger context window (1.05M against 131K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or GLM 4.5 Air?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; GLM 4.5 Air costs $0.20 and $1.10. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GLM 4.5 Air?

DeepSeek V4 Flash 0423, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs GLM 4.5 Air comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and GLM 4.5 Air's on 0. Where only one model has a result, the page says so instead of naming a winner.

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