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DeepSeek V4 Pro 0423 vs GLM 4.6

DeepSeek V4 Pro 0423 leads GLM 4.6 on coding, 38.7 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 1.4x less per output token ($2.20 vs $2.976 per million). Updated October 22, 2026; 50 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0423 Replace GLM 4.6
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
50.0
Output $/M
$2.976
47
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
3
vs boards won of 50 shared

DeepSeek V4 Pro 0423 or GLM 4.6: which to pick

Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 1.4x cheaper ($2.20 vs $2.976 per million) and work measured by Design Arena: agents building full-stack apps or Design Arena: agents building Godot games, where it leads.

Model ADeepSeek V4 Pro 0423DeepSeek38.7/1005 independent benchmarks$0.57 per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
50
DeepSeek V4 Pro 0423 only
34
GLM 4.6 only
19
Like-for-like categories
8 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 Pro 0423 38.7 from 5 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 15.5 points apart on average over 8 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): DeepSeek V4 Pro 0423 49.9% against GLM 4.6 3.1%, 46.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0423 $2.976 against GLM 4.6 $2.20 per million output tokens, 1.4x apart.
Context window
DeepSeek V4 Pro 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 Pro 0423BarsGLM 4.6Ties
Coding80
Intelligence10
Agentic work02
Reasoning50
Math20
Knowledge80
Web design70
General161
All shared boards473
CodingLike-for-likeSix of these boards feed the Vibe Coding Index80
Coding benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LMArena WebDev14471341DeepSeek V4 Pro 0423
AA Coding Index59.445.8DeepSeek V4 Pro 0423
LiveCodeBench (Vals AI)87.5%81.0%DeepSeek V4 Pro 0423
SWE-bench Verified (Vals AI)77.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench 4 (Vals AI)11.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Vibe Code Bench (Vals AI)49.9%3.1%DeepSeek V4 Pro 0423
Code migration (Vals AI)26.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench 2.1 (Vals AI)50.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
SkillsBench (Vals AI)51.3%Not measuredOnly DeepSeek V4 Pro 0423 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
FrontierCode17.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
WeirdML48.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
ALE-Bench1006.1340.8DeepSeek V4 Pro 0423
LMArena Text: coding14701449DeepSeek V4 Pro 0423
LMArena Text: software and IT14691455DeepSeek V4 Pro 0423
LMArena WebDev: React1441Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena WebDev: HTML14351350DeepSeek V4 Pro 0423
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
AA Intelligence Index30.418.5DeepSeek V4 Pro 0423
Epoch Capabilities Index149.1Not measuredOnly DeepSeek V4 Pro 0423 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building web apps1000Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building full-stack apps9481029GLM 4.6
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 games10591180GLM 4.6
Finance Agent (Vals AI)44.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Tax Agent Bench (Vals AI)25.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
Legal Research Bench (Vals AI)23.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Excel Modeling Benchmark (Vals AI)51.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
τ²-Bench TelecomNot measured76.9%Only GLM 4.6 measured
Vending-Bench 2$3,285Not measuredOnly DeepSeek V4 Pro 0423 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 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
GPQA Diamond89.4%74.5%DeepSeek V4 Pro 0423
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
GPQA Diamond (Epoch AI run)90.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
Chess puzzles19.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Mystery game puzzles17.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: hard prompts14611440DeepSeek V4 Pro 0423
LMArena Text: expert14631432DeepSeek V4 Pro 0423
LMArena Text: hard prompts in English14661445DeepSeek V4 Pro 0423
Kagi LLM Benchmark53.5%45.7%DeepSeek V4 Pro 0423
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 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
OTIS Mock AIME96.7%Not measuredOnly DeepSeek V4 Pro 0423 measured
FrontierMath, tiers 1 to 345.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
FrontierMath, tier 42.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
ProofBench16.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: math14431432DeepSeek V4 Pro 0423
LMArena Text: mathematical work14551447DeepSeek V4 Pro 0423
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
Knowledge benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
MMLU Pro87.3%82.2%DeepSeek V4 Pro 0423
LegalBench (Vals AI)80.3%79.6%DeepSeek V4 Pro 0423
CaseLaw (Vals AI)59.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
CorpFin (Vals AI)61.4%56.8%DeepSeek V4 Pro 0423
TaxEval (Vals AI)72.1%66.2%DeepSeek V4 Pro 0423
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MedCode (Vals AI)40.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
SimpleQA Verified47.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: science14701456DeepSeek V4 Pro 0423
LMArena Text: medicine and healthcare14661455DeepSeek V4 Pro 0423
LMArena Text: legal and government14641448DeepSeek V4 Pro 0423
LMArena Text: business and finance14431416DeepSeek V4 Pro 0423
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
Design Arena: websites12341174DeepSeek V4 Pro 0423
Design Arena: UI components12191145DeepSeek V4 Pro 0423
Design Arena: game dev12281150DeepSeek V4 Pro 0423
Design Arena: data viz12031161DeepSeek V4 Pro 0423
Design Arena: 3D12531128DeepSeek V4 Pro 0423
Design Arena: all code categories12401165DeepSeek V4 Pro 0423
Design Arena: SVG11391108DeepSeek V4 Pro 0423
Design Arena: ASCII art1149Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index161
General benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 0423GLM 4.6Leader
Public Benefits Bench (Vals AI)62.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
MedScribe (Vals AI)75.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
IFBenchNot measured43.4%Only GLM 4.6 measured
Long context reasoning (AA-LCR)Not measured54.0%Only GLM 4.6 measured
DTBench90.7%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMCA41.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
Surface Evolver Bench40.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
CL-bench Life13.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text14511440DeepSeek V4 Pro 0423
LMArena Text: instruction following14451410DeepSeek V4 Pro 0423
LMArena Text: creative writing14461412DeepSeek V4 Pro 0423
LMArena Text: English14591449DeepSeek V4 Pro 0423
LMArena Text: non-English14391426DeepSeek V4 Pro 0423
LMArena Text: Chinese14811499GLM 4.6
LMArena Text: German14581447DeepSeek V4 Pro 0423
LMArena Text: Japanese14461393DeepSeek V4 Pro 0423
LMArena Text: Korean14091400DeepSeek V4 Pro 0423
LMArena Text: French14731459DeepSeek V4 Pro 0423
LMArena Text: Spanish14571436DeepSeek V4 Pro 0423
LMArena Text: Russian14531418DeepSeek V4 Pro 0423
LMArena Text: Polish14611447DeepSeek V4 Pro 0423
LMArena Text: multi-turn14681427DeepSeek V4 Pro 0423
LMArena Text: longer queries14581422DeepSeek V4 Pro 0423
LMArena Text: writing and language14471415DeepSeek V4 Pro 0423
LMArena Text: entertainment and media14311409DeepSeek V4 Pro 0423
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Pro 0423 and GLM 4.6
BenchmarkDeepSeek V4 Pro 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 Pro 0423$0.0028Fits in one request
GLM 4.6$0.0017Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0423$0.077Fits in one request
GLM 4.6$0.037Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0423$0.301Fits in one request
GLM 4.6$0.142Exceeds the context window

GLM 4.6 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 Pro 0423 and GLM 4.6
SpecificationDeepSeek V4 Pro 0423Z.ai GLM 4.6
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026September 30, 2025
Context window1.05M205K
Input $/Mtok$1.358$0.60
Output $/Mtok$2.976$2.20
Coding index38.78.8
Independent measurements behind it52
Cost per solved task$0.57Not computable
SourceOpenRouter listingOpenRouter listing

Questions

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

Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 1.4x cheaper ($2.20 vs $2.976 per million) and work measured by Design Arena: agents building full-stack apps or Design Arena: agents building Godot games, where it leads.

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

DeepSeek V4 Pro 0423 costs $1.358 per million input tokens and $2.976 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for DeepSeek V4 Pro 0423 only.

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

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

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

50 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks 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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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v4-pro-vs-glm-4-6">LLMBenchmark.ai, DeepSeek V4 Pro 0423 vs GLM 4.6</a></p>