DeepSeek V4 Flash 0731 vs GLM 5.3 Flash

GLM 5.3 Flash leads DeepSeek V4 Flash 0731 on coding, 57.7 to 51.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 1.8x less per output token ($0.28 vs $0.50 per million). Updated October 21, 2026; 47 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0731 Replace GLM 5.3 Flash

DeepSeek V4 Flash 0731DeepSeek

Coding: 51.8
Overall: 55.2
Output $/M: $0.28

GLM 5.3 FlashZ.ai

Coding: 57.7
Overall: 66.0
Output $/M: $0.50

vs boards won of 47 shared, 1 tied

DeepSeek V4 Flash 0731 or GLM 5.3 Flash: which to pick

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731.

Pick DeepSeek V4 Flash 0731 for output tokens 1.8x cheaper ($0.28 vs $0.50 per million) and a lower cost per solved task ($0.01 against $0.02).

Model ADeepSeek V4 Flash 0731DeepSeek51.8/1004 independent benchmarks$0.01 per solved task Model BGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task

47855

Shared results: 47
DeepSeek V4 Flash 0731 only: 8
GLM 5.3 Flash only: 55
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.

Coding
Vibe Coding Index, six public coding benchmarks
GLM 5.3 Flash
GLM 5.3 Flash scores 57.7 against 51.8.
4 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 34.3.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 50.9 against 41.0.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 89.9% against 86.4%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 86.2% against 86.1%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3 Flash
GLM 5.3 Flash leads, 1272 against 1238.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, GLM 5.3 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, GLM 5.3 Flash $0.02.
Published attempt cost and pass rate

At a glance

Coding index: DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, GLM 5.3 Flash 57.7 from 6 benchmarks.
Widest category: Coding, 13.8 points apart on average over 14 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): DeepSeek V4 Flash 0731 74.7% against GLM 5.3 Flash 30.8%, 44.0 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Flash 0731 $0.28 against GLM 5.3 Flash $0.50 per million output tokens, 1.8x apart.
Context window: Both take 1.05M tokens.

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
Category	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Ties
Coding	7	6	1 tie
Intelligence	1	1
Agentic work	2	4
Reasoning	4	4
Math	4	0
Knowledge	1	2
Web design	0	8
General	0	2
All shared boards	19	27	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index76

Coding benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
LiveBench coding	Not measured	80.6%	Only GLM 5.3 Flash measured
LMArena WebDev	Not measured	1607	Only GLM 5.3 Flash measured
AA Coding Index	69.1	71.5	GLM 5.3 Flash
LiveCodeBench (Vals AI)	87.3%	80.5%	DeepSeek V4 Flash 0731
SWE-bench Verified (Vals AI)	88.8%	92.0%	GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)	18.7%	37.4%	GLM 5.3 Flash
Vibe Code Bench (Vals AI)	74.7%	30.8%	DeepSeek V4 Flash 0731
Code migration (Vals AI)	38.6%	20.5%	DeepSeek V4 Flash 0731
ProgramBench (Vals AI)	0.0%	0.0%	Tie
IOI (Vals AI)	32.7%	52.5%	GLM 5.3 Flash
Terminal-Bench 2.1 (Vals AI)	67.0%	62.9%	DeepSeek V4 Flash 0731
Vibe Code Bench 1-100 (Vals AI)	Not measured	16.0%	Only GLM 5.3 Flash measured
SkillsBench (Vals AI)	50.7%	40.2%	DeepSeek V4 Flash 0731
CyberBench (Vals AI)	72.1%	67.9%	DeepSeek V4 Flash 0731
SciCode	50.3%	51.6%	GLM 5.3 Flash
FrontierCode	18.8%	31.8%	GLM 5.3 Flash
FrontierSWE	Not measured	18.1%	Only GLM 5.3 Flash measured
WeirdML	63.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
ALE-Bench	1306.1	303.6	DeepSeek V4 Flash 0731
LMArena Text: coding	Not measured	1507	Only GLM 5.3 Flash measured
LMArena Text: software and IT	Not measured	1500	Only GLM 5.3 Flash measured
LMArena WebDev: React	Not measured	1624	Only GLM 5.3 Flash measured
LMArena WebDev: HTML	Not measured	1577	Only GLM 5.3 Flash measured
LMArena WebDev: from an image	Not measured	1578	Only GLM 5.3 Flash measured
Neither model has a result on the other 15 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11

Intelligence benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
AA Intelligence Index	34.3	41.8	GLM 5.3 Flash
Epoch Capabilities Index	154.8	153.1	DeepSeek V4 Flash 0731

Agentic workLike-for-likePublic boards, shown as published, kept out of the index24

Agentic work benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
AA Agentic Index	41.0	50.9	GLM 5.3 Flash
LiveBench research	Not measured	70.1%	Only GLM 5.3 Flash measured
LiveBench browser	Not measured	84.0%	Only GLM 5.3 Flash measured
LiveBench long agentic	Not measured	28.4%	Only GLM 5.3 Flash measured
SREBench (Vals AI)	Not measured	0.8%	Only GLM 5.3 Flash measured
Finance Agent (Vals AI)	49.5%	57.9%	GLM 5.3 Flash
Tax Agent Bench (Vals AI)	28.1%	31.6%	GLM 5.3 Flash
Legal Research Bench (Vals AI)	30.3%	45.2%	GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	10.4%	Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)	57.0%	55.9%	DeepSeek V4 Flash 0731
BioMysteryBench (Vals AI)	64.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)	4.3%	2.9%	DeepSeek V4 Flash 0731
APEX-Agents	Not measured	52.8%	Only GLM 5.3 Flash measured
Neither model has a result on the other 28 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index44

Reasoning benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
GPQA Diamond	89.9%	86.4%	DeepSeek V4 Flash 0731
LiveBench reasoning	Not measured	77.6%	Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)	Not measured	86.0%	Only GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)	90.8%	91.2%	GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)	38.6%	39.9%	GLM 5.3 Flash
GPQA Diamond (Epoch AI run)	91.0%	90.2%	DeepSeek V4 Flash 0731
ARC-AGI	89.0%	91.0%	GLM 5.3 Flash
ARC-AGI-2	61.4%	65.8%	GLM 5.3 Flash
SimpleBench	61.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
Chess puzzles	32.0%	21.0%	DeepSeek V4 Flash 0731
Mystery game puzzles	34.0%	8.0%	DeepSeek V4 Flash 0731
LMArena Text: hard prompts	Not measured	1490	Only GLM 5.3 Flash measured
LMArena Text: expert	Not measured	1511	Only GLM 5.3 Flash measured
LMArena Text: hard prompts in English	Not measured	1488	Only GLM 5.3 Flash measured
LMArena Vision: diagrams	Not measured	1317	Only GLM 5.3 Flash measured
LMArena Vision: homework	Not measured	1318	Only 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 index40

Math benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
OTIS Mock AIME	94.4%	93.9%	DeepSeek V4 Flash 0731
FrontierMath, tiers 1 to 3	57.5%	55.8%	DeepSeek V4 Flash 0731
FrontierMath, tier 4	24.4%	17.1%	DeepSeek V4 Flash 0731
ProofBench	56.0%	21.0%	DeepSeek V4 Flash 0731
LMArena Text: math	Not measured	1503	Only GLM 5.3 Flash measured
LMArena Text: mathematical work	Not measured	1497	Only GLM 5.3 Flash measured
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index12

Knowledge benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
MMLU Pro	86.2%	86.1%	DeepSeek V4 Flash 0731
LegalBench (Vals AI)	77.7%	83.9%	GLM 5.3 Flash
CorpFin (Vals AI)	61.9%	Not measured	Only DeepSeek V4 Flash 0731 measured
TaxEval (Vals AI)	70.7%	75.6%	GLM 5.3 Flash
MedCode (Vals AI)	41.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
SimpleQA Verified	33.6%	Not measured	Only DeepSeek V4 Flash 0731 measured
LMArena Text: science	Not measured	1484	Only GLM 5.3 Flash measured
LMArena Text: medicine and healthcare	Not measured	1475	Only GLM 5.3 Flash measured
LMArena Text: legal and government	Not measured	1473	Only GLM 5.3 Flash measured
LMArena Text: business and finance	Not measured	1460	Only GLM 5.3 Flash measured
Neither model has a result on the other 8 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index08

Web design benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
Design Arena: websites	1238	1272	GLM 5.3 Flash
Design Arena: UI components	1235	1316	GLM 5.3 Flash
Design Arena: game dev	1208	1278	GLM 5.3 Flash
Design Arena: data viz	1180	1261	GLM 5.3 Flash
Design Arena: 3D	1209	1316	GLM 5.3 Flash
Design Arena: all code categories	1230	1282	GLM 5.3 Flash
Design Arena: SVG	1185	1284	GLM 5.3 Flash
Design Arena: ASCII art	1090	1268	GLM 5.3 Flash
LiveBench design	Not measured	77.2%	Only GLM 5.3 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index02

General benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
Vals Index	Not measured	50.9%	Only GLM 5.3 Flash measured
LiveBench data analysis	Not measured	76.4%	Only GLM 5.3 Flash measured
MedScribe (Vals AI)	80.4%	88.9%	GLM 5.3 Flash
Long context reasoning (AA-LCR)	79.7%	80.0%	GLM 5.3 Flash
DTBench	90.9%	Not measured	Only DeepSeek V4 Flash 0731 measured
LMCA	41.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
Surface Evolver Bench	Not measured	52.5%	Only GLM 5.3 Flash measured
LMArena Text	Not measured	1471	Only GLM 5.3 Flash measured
LMArena Text: instruction following	Not measured	1478	Only GLM 5.3 Flash measured
LMArena Text: creative writing	Not measured	1441	Only GLM 5.3 Flash measured
LMArena Vision	Not measured	1294	Only GLM 5.3 Flash measured
LMArena Text: English	Not measured	1474	Only GLM 5.3 Flash measured
LMArena Text: non-English	Not measured	1462	Only GLM 5.3 Flash measured
LMArena Text: Chinese	Not measured	1531	Only GLM 5.3 Flash measured
LMArena Text: German	Not measured	1462	Only GLM 5.3 Flash measured
LMArena Text: Japanese	Not measured	1444	Only GLM 5.3 Flash measured
LMArena Text: Korean	Not measured	1436	Only GLM 5.3 Flash measured
LMArena Text: French	Not measured	1491	Only GLM 5.3 Flash measured
LMArena Text: Spanish	Not measured	1475	Only GLM 5.3 Flash measured
LMArena Text: Russian	Not measured	1465	Only GLM 5.3 Flash measured
LMArena Text: Polish	Not measured	1450	Only GLM 5.3 Flash measured
LMArena Text: multi-turn	Not measured	1469	Only GLM 5.3 Flash measured
LMArena Text: longer queries	Not measured	1481	Only GLM 5.3 Flash measured
LMArena Text: writing and language	Not measured	1455	Only GLM 5.3 Flash measured
LMArena Text: entertainment and media	Not measured	1440	Only GLM 5.3 Flash measured
LMArena Vision: English	Not measured	1295	Only GLM 5.3 Flash measured
LMArena Vision: Chinese	Not measured	1363	Only GLM 5.3 Flash measured
LMArena Vision: reading text	Not measured	1299	Only GLM 5.3 Flash measured
LMArena Vision: humor	Not measured	1279	Only GLM 5.3 Flash measured
LMArena Vision: creative writing	Not measured	1270	Only GLM 5.3 Flash measured
Neither model has a result on the other 16 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for DeepSeek V4 Flash 0731 and GLM 5.3 Flash
Benchmark	DeepSeek V4 Flash 0731	GLM 5.3 Flash	Leader
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 0731$0.0003Fits in one request

GLM 5.3 Flash$0.0004Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request

GLM 5.3 Flash$0.0090Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request

GLM 5.3 Flash$0.035Fits in one request

DeepSeek V4 Flash 0731 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 0731 and GLM 5.3 Flash
Specification	DeepSeek V4 Flash 0731	Z.ai GLM 5.3 Flash
Maker	DeepSeek	Z.ai
Weights	Open weights	Open weights
Released	July 31, 2026	August 26, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.14	$0.15
Output $/Mtok	$0.28	$0.50
Coding index	51.8	57.7
Independent measurements behind it	4	6
Cost per solved task	$0.01	$0.02
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than GLM 5.3 Flash for coding?

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731. Pick DeepSeek V4 Flash 0731 for output tokens 1.8x cheaper ($0.28 vs $0.50 per million) and a lower cost per solved task ($0.01 against $0.02).

Which is cheaper, DeepSeek V4 Flash 0731 or GLM 5.3 Flash?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and GLM 5.3 Flash $0.02.

Which has the bigger context window, DeepSeek V4 Flash 0731 or GLM 5.3 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Flash 0731 vs GLM 5.3 Flash comparison based on?

47 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and GLM 5.3 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/deepseek-v4-flash-0731-vs-glm-5-3-flash" title="DeepSeek V4 Flash 0731 vs GLM 5.3 Flash, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
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DeepSeek V4 Flash 0731 or GLM 5.3 Flash: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next