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DeepSeek V4 Pro 0423 vs GLM 5

GLM 5 leads DeepSeek V4 Pro 0423 on coding, 41.7 to 38.7 on the Vibe Coding Index, at about the same output price ($3.20 vs $2.716 per million). Updated October 21, 2026; 58 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0423 Replace GLM 5
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
50.0
Output $/M
$2.716
43
GLM 5Z.ai
Coding
41.7
Overall
54.3
Output $/M
$3.20
15
vs boards won of 58 shared

DeepSeek V4 Pro 0423 or GLM 5: which to pick

Pick GLM 5 for coding: it scores 41.7 on the Vibe Coding Index against 38.7 for DeepSeek V4 Pro 0423, though on 3 benchmarks against 5.

Pick DeepSeek V4 Pro 0423 for output tokens 1.2x cheaper ($2.716 vs $3.20 per million) and a lower cost per solved task ($0.57 against $0.63).

Model ADeepSeek V4 Pro 0423DeepSeek38.7/1005 independent benchmarks$0.57 per solved taskModel BGLM 5Z.ai41.7/1003 independent benchmarks$0.63 per solved task
Shared results
58
DeepSeek V4 Pro 0423 only
26
GLM 5 only
18
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 5 41.7 from 3 benchmarks.
Widest category
Agentic work, 13.2 points apart on average over 3 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): DeepSeek V4 Pro 0423 49.9% against GLM 5 23.4%, 26.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0423 $2.716 against GLM 5 $3.20 per million output tokens, 1.2x apart.
Context window
DeepSeek V4 Pro 0423 takes 1.05M tokens, GLM 5 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 5Ties
Coding91
Intelligence20
Agentic work03
Reasoning51
Math30
Knowledge72
Web design26
General152
All shared boards4315
CodingLike-for-likeSix of these boards feed the Vibe Coding Index91
Coding benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
SWE-bench VerifiedNot measured72.8%Only GLM 5 measured
SWE-bench MultilingualNot measured69.7%Only GLM 5 measured
LMArena WebDev14471435DeepSeek V4 Pro 0423
AA Coding Index59.4Not measuredOnly DeepSeek V4 Pro 0423 measured
LiveCodeBench (Vals AI)87.5%81.9%DeepSeek V4 Pro 0423
SWE-bench Verified (Vals AI)77.4%71.4%DeepSeek V4 Pro 0423
Terminal-Bench 4 (Vals AI)11.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Vibe Code Bench (Vals AI)49.9%23.4%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
Terminal-Bench Hard (Artificial Analysis run)Not measured43.2%Only GLM 5 measured
Terminal-BenchNot measured52.4%Only GLM 5 measured
FrontierCode17.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
WeirdML48.9%48.2%DeepSeek V4 Pro 0423
ALE-Bench1006.1765.6DeepSeek V4 Pro 0423
LMArena Text: coding14701461DeepSeek V4 Pro 0423
LMArena Text: software and IT14691460DeepSeek V4 Pro 0423
LMArena WebDev: React14411424DeepSeek V4 Pro 0423
LMArena WebDev: HTML14351450GLM 5
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
AA Intelligence Index30.427.9DeepSeek V4 Pro 0423
Epoch Capabilities Index149.1145.8DeepSeek V4 Pro 0423
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
Agentic work benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
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 apps9481123GLM 5
Design Arena: agents building mobile appsNot measured1136Only GLM 5 measured
Design Arena: agents building Android appsNot measured1146Only GLM 5 measured
Design Arena: agents building Godot games10591144GLM 5
Design Arena: HTML slidesNot measured1148Only GLM 5 measured
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 measured98.2%Only GLM 5 measured
Vending-Bench 2$3,285$4,432GLM 5
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
GPQA Diamond89.4%83.3%DeepSeek V4 Pro 0423
GPQA Diamond (Artificial Analysis run)Not measured82.0%Only GLM 5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured29.3%Only GLM 5 measured
GPQA Diamond (Epoch AI run)90.9%87.8%DeepSeek V4 Pro 0423
ARC-AGINot measured44.7%Only GLM 5 measured
ARC-AGI-2Not measured4.9%Only GLM 5 measured
SimpleBenchNot measured53.2%Only GLM 5 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 prompts14611452DeepSeek V4 Pro 0423
LMArena Text: expert14631454DeepSeek V4 Pro 0423
LMArena Text: hard prompts in English14661460DeepSeek V4 Pro 0423
Kagi LLM Benchmark53.5%75.0%GLM 5
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
AIMENot measured91.7%Only GLM 5 measured
OTIS Mock AIME96.7%80.0%DeepSeek V4 Pro 0423
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: math14431440DeepSeek V4 Pro 0423
LMArena Text: mathematical work14551451DeepSeek V4 Pro 0423
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72
Knowledge benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
MMLU Pro87.3%86.0%DeepSeek V4 Pro 0423
LegalBench (Vals AI)80.3%84.1%GLM 5
CaseLaw (Vals AI)59.4%52.5%DeepSeek V4 Pro 0423
CorpFin (Vals AI)61.4%62.9%GLM 5
TaxEval (Vals AI)72.1%70.0%DeepSeek V4 Pro 0423
MedQA (Vals AI)Not measured94.3%Only GLM 5 measured
MedCode (Vals AI)40.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
SimpleQA Verified47.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: science14701460DeepSeek V4 Pro 0423
LMArena Text: medicine and healthcare14661455DeepSeek V4 Pro 0423
LMArena Text: legal and government14641453DeepSeek V4 Pro 0423
LMArena Text: business and finance14431430DeepSeek V4 Pro 0423
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index26
Web design benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
Design Arena: websites12341247GLM 5
Design Arena: UI components12221230GLM 5
Design Arena: game dev12291234GLM 5
Design Arena: data viz12031228GLM 5
Design Arena: 3D12541229DeepSeek V4 Pro 0423
Design Arena: all code categories12401246GLM 5
Design Arena: SVG11401168GLM 5
Design Arena: ASCII art11491147DeepSeek V4 Pro 0423
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index152
General benchmarks for DeepSeek V4 Pro 0423 and GLM 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
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 measured72.3%Only GLM 5 measured
Long context reasoning (AA-LCR)Not measured75.7%Only GLM 5 measured
DTBench90.7%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMCA41.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
CL-benchNot measured18.7%Only GLM 5 measured
Surface Evolver Bench40.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
CL-bench Life13.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text14511446DeepSeek V4 Pro 0423
LMArena Text: instruction following14451428DeepSeek V4 Pro 0423
LMArena Text: creative writing14461438DeepSeek V4 Pro 0423
LMArena Text: English14591458DeepSeek V4 Pro 0423
LMArena Text: non-English14391430DeepSeek V4 Pro 0423
LMArena Text: Chinese14811511GLM 5
LMArena Text: German14581447DeepSeek V4 Pro 0423
LMArena Text: Japanese14461416DeepSeek V4 Pro 0423
LMArena Text: Korean14091423GLM 5
LMArena Text: French14731456DeepSeek V4 Pro 0423
LMArena Text: Spanish14571454DeepSeek V4 Pro 0423
LMArena Text: Russian14531436DeepSeek V4 Pro 0423
LMArena Text: Polish14611434DeepSeek V4 Pro 0423
LMArena Text: multi-turn14681456DeepSeek V4 Pro 0423
LMArena Text: longer queries14581446DeepSeek V4 Pro 0423
LMArena Text: writing and language14471437DeepSeek V4 Pro 0423
LMArena Text: entertainment and media14311426DeepSeek V4 Pro 0423
Neither model has a result on the other 20 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 5
BenchmarkDeepSeek V4 Pro 0423GLM 5Leader
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$0.0026Fits in one request
GLM 5$0.0026Fits in one request

DeepSeek V4 Pro 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0423$0.069Fits in one request
GLM 5$0.060Fits in one request

GLM 5 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0423$0.272Fits in one request
GLM 5$0.232Exceeds the context window

GLM 5 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 5
SpecificationDeepSeek V4 Pro 0423Z.ai GLM 5
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026February 11, 2026
Context window1.05M205K
Input $/Mtok$1.225$1.00
Output $/Mtok$2.716$3.20
Coding index38.741.7
Independent measurements behind it53
Cost per solved task$0.57$0.63
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0423 better than GLM 5 for coding?

Pick GLM 5 for coding: it scores 41.7 on the Vibe Coding Index against 38.7 for DeepSeek V4 Pro 0423, though on 3 benchmarks against 5. Pick DeepSeek V4 Pro 0423 for output tokens 1.2x cheaper ($2.716 vs $3.20 per million) and a lower cost per solved task ($0.57 against $0.63).

Which is cheaper, DeepSeek V4 Pro 0423 or GLM 5?

DeepSeek V4 Pro 0423 costs $1.225 per million input tokens and $2.716 per million output tokens; GLM 5 costs $1.00 and $3.20. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0423 costs $0.57 and GLM 5 $0.63.

Which has the bigger context window, DeepSeek V4 Pro 0423 or GLM 5?

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

How many benchmarks is the DeepSeek V4 Pro 0423 vs GLM 5 comparison based on?

58 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and GLM 5's on 3. 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-5">LLMBenchmark.ai, DeepSeek V4 Pro 0423 vs GLM 5</a></p>