Enter opens the highlighted result. Esc closes.

DeepSeek V3 0324 vs GLM 4.6V

GLM 4.6V leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 11.2 to 9.7, at about the same output price ($0.90 vs $1.07 per million). Updated October 21, 2026; 11 benchmarks have a result for both.

Replace DeepSeek V3 0324 Replace GLM 4.6V
DeepSeek V3 0324DeepSeek
Coding
No data
Overall
No data
Output $/M
$1.07
4
GLM 4.6VZ.ai
Coding
No data
Overall
No data
Output $/M
$0.90
7
vs boards won of 11 shared

DeepSeek V3 0324 or GLM 4.6V: which to pick

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

Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Model ADeepSeek V3 0324DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 4.6VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
11
DeepSeek V3 0324 only
24
GLM 4.6V only
27
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 V3 0324 not benchmarked, GLM 4.6V not benchmarked.
Widest category
Math, 44.3 points apart on average over 2 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): DeepSeek V3 0324 41.0% against GLM 4.6V 85.3%, 44.3 points apart on a 0 to 100 scale.
Output price
DeepSeek V3 0324 $1.07 against GLM 4.6V $0.90 per million output tokens, 1.2x apart.
Context window
DeepSeek V3 0324 takes 164K tokens, GLM 4.6V 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 V3 0324BarsGLM 4.6VTies
Coding11
Intelligence01
Agentic work10
Reasoning02
Math02
Knowledge10
General11
All shared boards47
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
SWE-bench Verified42.0%Not measuredOnly DeepSeek V3 0324 measured
AA Coding Index21.2Not measuredOnly DeepSeek V3 0324 measured
LiveCodeBench (Vals AI)65.5%Not measuredOnly DeepSeek V3 0324 measured
LiveCodeBench (Artificial Analysis run)40.5%41.1%GLM 4.6V
SciCode39.0%Not measuredOnly DeepSeek V3 0324 measured
Terminal-Bench Hard (Artificial Analysis run)15.2%14.4%DeepSeek V3 0324
WeirdML36.1%Not measuredOnly DeepSeek V3 0324 measured
LMArena Text: codingNot measured1389Only GLM 4.6V measured
LMArena Text: software and ITNot measured1391Only GLM 4.6V measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
AA Intelligence Index9.711.2GLM 4.6V
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
AA Agentic Index0.8Not measuredOnly DeepSeek V3 0324 measured
τ²-Bench Telecom47.1%31.6%DeepSeek V3 0324
METR time horizons49.6%Not measuredOnly DeepSeek V3 0324 measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
GPQA Diamond61.6%Not measuredOnly DeepSeek V3 0324 measured
GPQA Diamond (Artificial Analysis run)65.5%71.9%GLM 4.6V
Humanity's Last Exam (Artificial Analysis run)4.7%9.6%GLM 4.6V
GPQA Diamond (Epoch AI run)67.6%Not measuredOnly DeepSeek V3 0324 measured
SimpleBench27.2%Not measuredOnly DeepSeek V3 0324 measured
LMArena Text: hard promptsNot measured1367Only GLM 4.6V measured
LMArena Text: expertNot measured1371Only GLM 4.6V measured
LMArena Text: hard prompts in EnglishNot measured1391Only GLM 4.6V measured
LMArena Vision: diagramsNot measured1182Only GLM 4.6V measured
LMArena Vision: homeworkNot measured1155Only GLM 4.6V measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
AIME52.2%Not measuredOnly DeepSeek V3 0324 measured
MATH 500 (Vals AI)88.6%Not measuredOnly DeepSeek V3 0324 measured
MGSM (Vals AI)91.7%Not measuredOnly DeepSeek V3 0324 measured
AA Math Index41.085.3GLM 4.6V
AIME 2025 (Artificial Analysis run)41.0%85.3%GLM 4.6V
OTIS Mock AIME37.8%Not measuredOnly DeepSeek V3 0324 measured
MATH level 575.5%Not measuredOnly DeepSeek V3 0324 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
MMLU Pro79.5%Not measuredOnly DeepSeek V3 0324 measured
LegalBench (Vals AI)77.7%Not measuredOnly DeepSeek V3 0324 measured
CorpFin (Vals AI)54.7%Not measuredOnly DeepSeek V3 0324 measured
TaxEval (Vals AI)71.1%Not measuredOnly DeepSeek V3 0324 measured
MedQA (Vals AI)82.0%Not measuredOnly DeepSeek V3 0324 measured
MMLU Pro (Artificial Analysis run)81.9%79.9%DeepSeek V3 0324
LMArena Text: scienceNot measured1389Only GLM 4.6V measured
LMArena Text: medicine and healthcareNot measured1389Only GLM 4.6V measured
LMArena Text: legal and governmentNot measured1393Only GLM 4.6V measured
LMArena Text: business and financeNot measured1359Only GLM 4.6V measured
Neither model has a result on the other 8 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
IFBench41.0%30.1%DeepSeek V3 0324
Long context reasoning (AA-LCR)40.7%48.7%GLM 4.6V
DTBench64.8%Not measuredOnly DeepSeek V3 0324 measured
LMCA15.5%Not measuredOnly DeepSeek V3 0324 measured
Fiction.LiveBench50.0%Not measuredOnly DeepSeek V3 0324 measured
Creative writing (Lech Mazur)77.0%Not measuredOnly DeepSeek V3 0324 measured
LMArena TextNot measured1376Only GLM 4.6V measured
LMArena Text: instruction followingNot measured1350Only GLM 4.6V measured
LMArena Text: creative writingNot measured1347Only GLM 4.6V measured
LMArena VisionNot measured1164Only GLM 4.6V measured
LMArena Text: EnglishNot measured1395Only GLM 4.6V measured
LMArena Text: non-EnglishNot measured1358Only GLM 4.6V measured
LMArena Text: ChineseNot measured1425Only GLM 4.6V measured
LMArena Text: RussianNot measured1339Only GLM 4.6V measured
LMArena Text: multi-turnNot measured1359Only GLM 4.6V measured
LMArena Text: longer queriesNot measured1357Only GLM 4.6V measured
LMArena Text: writing and languageNot measured1347Only GLM 4.6V measured
LMArena Text: entertainment and mediaNot measured1343Only GLM 4.6V measured
LMArena Vision: EnglishNot measured1179Only GLM 4.6V measured
LMArena Vision: ChineseNot measured1217Only GLM 4.6V measured
LMArena Vision: reading textNot measured1171Only GLM 4.6V measured
LMArena Vision: creative writingNot measured1113Only GLM 4.6V measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3 0324 and GLM 4.6V
BenchmarkDeepSeek V3 0324GLM 4.6VLeader
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 V3 0324$0.0008Fits in one request
GLM 4.6V$0.0008Fits in one request

GLM 4.6V costs less

Repository review

50K input + 3K output tokens

DeepSeek V3 0324$0.017Fits in one request
GLM 4.6V$0.018Fits in one request

DeepSeek V3 0324 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3 0324$0.065Exceeds the context window
GLM 4.6V$0.069Exceeds the context window

DeepSeek V3 0324 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 V3 0324 and GLM 4.6V
SpecificationDeepSeek V3 0324Z.ai GLM 4.6V
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedMarch 24, 2025December 8, 2025
Context window164K131K
Input $/Mtok$0.27$0.30
Output $/Mtok$1.07$0.90
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3 0324 better than GLM 4.6V for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for a larger context window (164K against 131K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, DeepSeek V3 0324 or GLM 4.6V?

DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; GLM 4.6V costs $0.30 and $0.90. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3 0324 or GLM 4.6V?

DeepSeek V3 0324, with 164K tokens against 131K.

How many benchmarks is the DeepSeek V3 0324 vs GLM 4.6V comparison based on?

11 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and GLM 4.6V's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next