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DeepSeek V3.2 vs GLM 5.3 Flash

Updated October 21, 2026. 55 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V3.2 Replace GLM 5.3 Flash
DeepSeek V3.2DeepSeek
Coding
54.4
Overall
21.5
Output $/M
$0.42
1
GLM 5.3 FlashZ.ai
Coding
71.0
Overall
41.8
Output $/M
$0.50
54
vs boards won of 55 shared

Decision reading

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 54.4 for DeepSeek V3.2.

Pick DeepSeek V3.2 when output tokens cost 1.2x less, or when the benchmark that matters is LiveCodeBench (Vals AI), where it leads.

Model ADeepSeek V3.2DeepSeek54.4/1002 independent benchmarks$0.99 per solved taskModel BGLM 5.3 FlashZ.ai71.0/1002 independent benchmarks$0.02 per solved task
Shared results
55
DeepSeek V3.2 only
20
GLM 5.3 Flash only
47
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 V3.2 54.4 from 2 benchmarks, GLM 5.3 Flash 71.0 from 2 benchmarks.
Widest category
Agentic work, 31.5 points apart on average over 1 shared benchmark.
Widest single gap
ARC-AGI-2: DeepSeek V3.2 4.0% against GLM 5.3 Flash 65.8%, 61.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.42 against GLM 5.3 Flash $0.50 per million output tokens, 1.2x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GLM 5.3 Flash 1.05M.

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 V3.2BarsGLM 5.3 FlashTies
Coding18
Intelligence02
Agentic work01
Reasoning08
Math02
Knowledge07
Web design08
General018
All shared boards154
CodingLike-for-likeFour of these boards feed the Vibe Coding Index18
Coding benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LiveBench codingNot measured80.6%Only GLM 5.3 Flash measured
LMArena WebDev13621607GLM 5.3 Flash
AA Coding Index44.271.5GLM 5.3 Flash
LiveCodeBench (Vals AI)80.7%80.5%DeepSeek V3.2
SWE-bench Verified (Vals AI)67.6%92.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)Not measured37.4%Only GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)5.1%30.8%GLM 5.3 Flash
Code migration (Vals AI)Not measured20.5%Only GLM 5.3 Flash measured
ProgramBench (Vals AI)Not measured0.0%Only GLM 5.3 Flash measured
IOI (Vals AI)Not measured52.5%Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured62.9%Only GLM 5.3 Flash measured
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)Not measured40.2%Only GLM 5.3 Flash measured
CyberBench (Vals AI)Not measured67.9%Only GLM 5.3 Flash measured
LiveCodeBench (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SciCodeNot measured51.6%Only GLM 5.3 Flash measured
Terminal-Bench Hard (Artificial Analysis run)35.6%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
FrontierCodeNot measured31.8%Only GLM 5.3 Flash measured
FrontierSWENot measured18.1%Only GLM 5.3 Flash measured
ALE-BenchNot measured303.6Only GLM 5.3 Flash measured
LMArena Text: coding14531507GLM 5.3 Flash
LMArena Text: software and IT14491500GLM 5.3 Flash
LMArena WebDev: React13501624GLM 5.3 Flash
LMArena WebDev: HTML13711577GLM 5.3 Flash
LMArena WebDev: from an imageNot measured1578Only GLM 5.3 Flash measured
Neither model has a result on the other 10 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
AA Intelligence Index21.541.8GLM 5.3 Flash
Epoch Capabilities Index146.1153.1GLM 5.3 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
AA Agentic IndexNot measured50.9Only GLM 5.3 Flash measured
LiveBench researchNot measured70.1%Only GLM 5.3 Flash measured
LiveBench browserNot measured84.0%Only GLM 5.3 Flash measured
LiveBench long agenticNot measured28.4%Only GLM 5.3 Flash measured
SREBench (Vals AI)Not measured0.8%Only GLM 5.3 Flash measured
Finance Agent (Vals AI)Not measured57.9%Only GLM 5.3 Flash measured
Tax Agent Bench (Vals AI)Not measured31.6%Only GLM 5.3 Flash measured
Legal Research Bench (Vals AI)Not measured45.2%Only GLM 5.3 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured10.4%Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)Not measured55.9%Only GLM 5.3 Flash measured
Terminal-Bench-Science (Vals AI)Not measured2.9%Only GLM 5.3 Flash measured
τ²-Bench Telecom90.6%Not measuredOnly DeepSeek V3.2 measured
APEX-Agents21.3%52.8%GLM 5.3 Flash
Vending-Bench 2$1,034Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
GPQA Diamond80.3%86.4%GLM 5.3 Flash
LiveBench reasoningNot measured77.6%Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)Not measured86.0%Only GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)84.0%91.2%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)24.6%39.9%GLM 5.3 Flash
GPQA Diamond (Epoch AI run)Not measured90.2%Only GLM 5.3 Flash measured
ARC-AGI57.0%91.0%GLM 5.3 Flash
ARC-AGI-24.0%65.8%GLM 5.3 Flash
Chess puzzlesNot measured21.0%Only GLM 5.3 Flash measured
Mystery game puzzlesNot measured8.0%Only GLM 5.3 Flash measured
LMArena Text: hard prompts14341490GLM 5.3 Flash
LMArena Text: expert14361511GLM 5.3 Flash
LMArena Text: hard prompts in English14461488GLM 5.3 Flash
LMArena Vision: diagramsNot measured1317Only GLM 5.3 Flash measured
LMArena Vision: homeworkNot measured1318Only GLM 5.3 Flash measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured93.9%Only GLM 5.3 Flash measured
FrontierMath, tiers 1 to 3Not measured55.8%Only GLM 5.3 Flash measured
FrontierMath, tier 4Not measured17.1%Only GLM 5.3 Flash measured
ProofBenchNot measured21.0%Only GLM 5.3 Flash measured
LMArena Text: math14351503GLM 5.3 Flash
LMArena Text: mathematical work14401497GLM 5.3 Flash
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index07
Knowledge benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
MMLU Pro84.9%86.1%GLM 5.3 Flash
LegalBench (Vals AI)76.1%83.9%GLM 5.3 Flash
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%75.6%GLM 5.3 Flash
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: science14461484GLM 5.3 Flash
LMArena Text: medicine and healthcare14401475GLM 5.3 Flash
LMArena Text: legal and government14251473GLM 5.3 Flash
LMArena Text: business and finance14101460GLM 5.3 Flash
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
Design Arena: websites11751272GLM 5.3 Flash
Design Arena: UI components11491316GLM 5.3 Flash
Design Arena: game dev11321279GLM 5.3 Flash
Design Arena: data viz11581262GLM 5.3 Flash
Design Arena: 3D11331316GLM 5.3 Flash
Design Arena: all code categories11641282GLM 5.3 Flash
Design Arena: SVG10321284GLM 5.3 Flash
Design Arena: ASCII art10821269GLM 5.3 Flash
LiveBench designNot measured77.2%Only GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysisNot measured76.4%Only GLM 5.3 Flash measured
MedScribe (Vals AI)Not measured88.9%Only GLM 5.3 Flash measured
IFBench60.7%Not measuredOnly DeepSeek V3.2 measured
Long context reasoning (AA-LCR)73.3%80.0%GLM 5.3 Flash
DTBench85.6%Not measuredOnly DeepSeek V3.2 measured
LMCA28.8%Not measuredOnly DeepSeek V3.2 measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
Surface Evolver BenchNot measured52.5%Only GLM 5.3 Flash measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251471GLM 5.3 Flash
LMArena Text: instruction following14131478GLM 5.3 Flash
LMArena Text: creative writing14001441GLM 5.3 Flash
LMArena VisionNot measured1294Only GLM 5.3 Flash measured
LMArena Text: English14391474GLM 5.3 Flash
LMArena Text: non-English14091462GLM 5.3 Flash
LMArena Text: Chinese14551531GLM 5.3 Flash
LMArena Text: German14131462GLM 5.3 Flash
LMArena Text: Japanese13741444GLM 5.3 Flash
LMArena Text: Korean13701436GLM 5.3 Flash
LMArena Text: French14291491GLM 5.3 Flash
LMArena Text: Spanish14241475GLM 5.3 Flash
LMArena Text: Russian14241465GLM 5.3 Flash
LMArena Text: Polish14191450GLM 5.3 Flash
LMArena Text: multi-turn14271469GLM 5.3 Flash
LMArena Text: longer queries14281481GLM 5.3 Flash
LMArena Text: writing and language14071455GLM 5.3 Flash
LMArena Text: entertainment and media13951440GLM 5.3 Flash
LMArena Vision: EnglishNot measured1295Only GLM 5.3 Flash measured
LMArena Vision: ChineseNot measured1363Only GLM 5.3 Flash measured
LMArena Vision: reading textNot measured1299Only GLM 5.3 Flash measured
LMArena Vision: humorNot measured1279Only GLM 5.3 Flash measured
LMArena Vision: creative writingNot measured1270Only GLM 5.3 Flash measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and GLM 5.3 Flash
BenchmarkDeepSeek V3.2GLM 5.3 FlashLeader
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 V3.2$0.0005Fits in one request
GLM 5.3 Flash$0.0004Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.015Fits in one request
GLM 5.3 Flash$0.0090Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.060Exceeds the context window
GLM 5.3 Flash$0.035Fits in one request

GLM 5.3 Flash 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 V3.2 and GLM 5.3 Flash
SpecificationDeepSeek V3.2Z.ai GLM 5.3 Flash
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedDecember 1, 2025August 26, 2026
Context window164K1.05M
Input $/Mtok$0.28$0.15
Output $/Mtok$0.42$0.50
Coding index54.471.0
Independent measurements behind it22
Cost per solved task$0.99$0.02
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GLM 5.3 Flash for coding?

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 54.4 for DeepSeek V3.2. Pick DeepSeek V3.2 when output tokens cost 1.2x less, or when the benchmark that matters is LiveCodeBench (Vals AI), where it leads.

Which is cheaper, DeepSeek V3.2 or GLM 5.3 Flash?

DeepSeek V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, DeepSeek V3.2 costs $0.99 and GLM 5.3 Flash $0.02.

Which has the bigger context window, DeepSeek V3.2 or GLM 5.3 Flash?

GLM 5.3 Flash, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 vs GLM 5.3 Flash comparison based on?

55 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 2 independent benchmarks and GLM 5.3 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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