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DeepSeek V4 Flash 0423 vs GLM 4.6

DeepSeek V4 Flash 0423 leads GLM 4.6 on the Artificial Analysis Intelligence Index, 24.4 to 18.5, and DeepSeek V4 Flash 0423 costs 7.9x less per output token ($0.28 vs $2.20 per million). Updated October 21, 2026; 41 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace GLM 4.6
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
21
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
20
vs boards won of 41 shared

DeepSeek V4 Flash 0423 or GLM 4.6: which to pick

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 7.9x cheaper ($0.28 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
41
DeepSeek V4 Flash 0423 only
8
GLM 4.6 only
28
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 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 14.7 points apart on average over 6 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: DeepSeek V4 Flash 0423 1558 against GLM 4.6 1350, 34.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GLM 4.6 $2.20 per million output tokens, 7.9x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GLM 4.6 205K.

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 4.6Ties
Coding51
Intelligence10
Reasoning40
Math02
Knowledge13
Web design61
General413
All shared boards2120
CodingLike-for-likeSix of these boards feed the Vibe Coding Index51
Coding benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LMArena WebDev15821341DeepSeek V4 Flash 0423
AA Coding Index52.045.8DeepSeek V4 Flash 0423
LiveCodeBench (Vals AI)Not measured81.0%Only GLM 4.6 measured
Vibe Code Bench (Vals AI)Not measured3.1%Only GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only GLM 4.6 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only GLM 4.6 measured
Terminal-BenchNot measured24.5%Only GLM 4.6 measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2340.8DeepSeek V4 Flash 0423
LMArena Text: coding14571449DeepSeek V4 Flash 0423
LMArena Text: software and IT14531455GLM 4.6
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML15581350DeepSeek V4 Flash 0423
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
AA Intelligence Index24.418.5DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile appsNot measured1096Only GLM 4.6 measured
Design Arena: agents building Android appsNot measured1084Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
τ²-Bench TelecomNot measured76.9%Only GLM 4.6 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured72.4%Only GLM 4.6 measured
BrowseComp-PlusNot measured48.2%Only GLM 4.6 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
GPQA DiamondNot measured74.5%Only GLM 4.6 measured
GPQA Diamond (Artificial Analysis run)Not measured78.0%Only GLM 4.6 measured
Humanity's Last Exam (Artificial Analysis run)Not measured14.5%Only GLM 4.6 measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441440DeepSeek V4 Flash 0423
LMArena Text: expert14411432DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491445DeepSeek V4 Flash 0423
Kagi LLM Benchmark52.2%45.7%DeepSeek 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 index02
Math benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
AIMENot measured92.7%Only GLM 4.6 measured
MGSM (Vals AI)Not measured89.8%Only GLM 4.6 measured
AA Math IndexNot measured86.0Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)Not measured86.0%Only GLM 4.6 measured
LMArena Text: math14261432GLM 4.6
LMArena Text: mathematical work14321447GLM 4.6
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
MMLU ProNot measured82.2%Only GLM 4.6 measured
LegalBench (Vals AI)Not measured79.6%Only GLM 4.6 measured
CorpFin (Vals AI)Not measured56.8%Only GLM 4.6 measured
TaxEval (Vals AI)Not measured66.2%Only GLM 4.6 measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
LMArena Text: science14461456GLM 4.6
LMArena Text: medicine and healthcare14481455GLM 4.6
LMArena Text: legal and government14391448GLM 4.6
LMArena Text: business and finance14251416DeepSeek V4 Flash 0423
Neither model has a result on the other 8 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 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
Design Arena: websites12081174DeepSeek V4 Flash 0423
Design Arena: UI components11651148DeepSeek V4 Flash 0423
Design Arena: game dev11971151DeepSeek V4 Flash 0423
Design Arena: data viz11271161GLM 4.6
Design Arena: 3D11891129DeepSeek V4 Flash 0423
Design Arena: all code categories12051166DeepSeek V4 Flash 0423
Design Arena: SVG11551109DeepSeek 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 index413
General benchmarks for DeepSeek V4 Flash 0423 and GLM 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
IFBenchNot measured43.4%Only GLM 4.6 measured
Long context reasoning (AA-LCR)Not measured54.0%Only GLM 4.6 measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text14321440GLM 4.6
LMArena Text: instruction following14211410DeepSeek V4 Flash 0423
LMArena Text: creative writing14031412GLM 4.6
LMArena Text: English14411449GLM 4.6
LMArena Text: non-English14191426GLM 4.6
LMArena Text: Chinese14631499GLM 4.6
LMArena Text: German14191447GLM 4.6
LMArena Text: Japanese13891393GLM 4.6
LMArena Text: Korean13831400GLM 4.6
LMArena Text: French14391459GLM 4.6
LMArena Text: Spanish14361436GLM 4.6
LMArena Text: Russian14271418DeepSeek V4 Flash 0423
LMArena Text: Polish14361447GLM 4.6
LMArena Text: multi-turn14491427DeepSeek V4 Flash 0423
LMArena Text: longer queries14341422DeepSeek V4 Flash 0423
LMArena Text: writing and language14101415GLM 4.6
LMArena Text: entertainment and media14001409GLM 4.6
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 4.6
BenchmarkDeepSeek V4 Flash 0423GLM 4.6Leader
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 4.6$0.0017Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0073Fits in one request
GLM 4.6$0.037Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.029Fits in one request
GLM 4.6$0.142Exceeds 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 4.6
SpecificationDeepSeek V4 Flash 0423Z.ai GLM 4.6
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026September 30, 2025
Context window1.05M205K
Input $/Mtok$0.13$0.60
Output $/Mtok$0.28$2.20
Coding indexNot benchmarked8.8
Independent measurements behind it12
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GLM 4.6 for coding?

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 7.9x cheaper ($0.28 vs $2.20 per million) and a larger context window (1.05M against 205K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or GLM 4.6?

DeepSeek V4 Flash 0423 costs $0.13 per million input tokens and $0.28 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GLM 4.6?

DeepSeek V4 Flash 0423, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs GLM 4.6 comparison based on?

41 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 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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