DeepSeek V4 Pro 0813 vs GLM 4.6

DeepSeek V4 Pro 0813 leads GLM 4.6 on coding, 56.1 to 8.8 on the Vibe Coding Index, at about the same output price ($1.98 vs $2.20 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0813 Replace GLM 4.6

DeepSeek V4 Pro 0813DeepSeek

Coding: 56.1
Overall: 60.8
Output $/M: $1.98

GLM 4.6Z.ai

Coding: 8.8
Overall: 33.4
Output $/M: $2.20

vs boards won of 40 shared

DeepSeek V4 Pro 0813 or GLM 4.6: which to pick

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for work measured by LMArena Text: mathematical work or LMArena Text: medicine and healthcare, where it leads.

Model ADeepSeek V4 Pro 0813DeepSeek56.1/1005 independent benchmarks$0.10 per solved task Model BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task

403829

Shared results: 40
DeepSeek V4 Pro 0813 only: 38
GLM 4.6 only: 29
Like-for-like categories: 6 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
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 scores 56.1 against 8.8.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 18.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0813 has a AA Agentic Index result, 41.3.
Directional only
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 92.4% against 74.5%.
Same board, both measured
Math
AIME
No call
Only GLM 4.6 has a AIME result, 92.7%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 87.0% against 82.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 4.6 has a Design Arena: websites result, 1174.
Directional only
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.0016, GLM 4.6 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0813 has the number, $0.10.
Directional only

At a glance

Coding index: DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category: Coding, 27.4 points apart on average over 8 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): DeepSeek V4 Pro 0813 82.3% against GLM 4.6 3.1%, 79.2 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Pro 0813 $1.98 against GLM 4.6 $2.20 per million output tokens, 1.1x apart.
Context window: DeepSeek V4 Pro 0813 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
Category	DeepSeek V4 Pro 0813	GLM 4.6
Coding	8	0
Intelligence	1	0
Reasoning	6	0
Math	1	1
Knowledge	7	1
General	12	3
All shared boards	35	5

CodingLike-for-likeSix of these boards feed the Vibe Coding Index80

Coding benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
SWE-bench Verified	Not measured	68.2%	Only GLM 4.6 measured
LMArena WebDev	1582	1341	DeepSeek V4 Pro 0813
AA Coding Index	68.8	45.8	DeepSeek V4 Pro 0813
LiveCodeBench (Vals AI)	87.5%	81.0%	DeepSeek V4 Pro 0813
SWE-bench Verified (Vals AI)	96.4%	Not measured	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 4 (Vals AI)	14.1%	Not measured	Only DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)	82.3%	3.1%	DeepSeek V4 Pro 0813
Code migration (Vals AI)	41.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
ProgramBench (Vals AI)	0.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
IOI (Vals AI)	51.6%	Not measured	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)	54.7%	Not measured	Only DeepSeek V4 Pro 0813 measured
Vibe Code Bench 1-100 (Vals AI)	17.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)	53.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)	72.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
LiveCodeBench (Artificial Analysis run)	Not measured	69.5%	Only GLM 4.6 measured
SciCode	51.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	28.8%	Only GLM 4.6 measured
Terminal-Bench	Not measured	24.5%	Only GLM 4.6 measured
FrontierCode	28.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
WeirdML	66.2%	Not measured	Only DeepSeek V4 Pro 0813 measured
ALE-Bench	1403.2	340.8	DeepSeek V4 Pro 0813
LMArena Text: coding	1469	1449	DeepSeek V4 Pro 0813
LMArena Text: software and IT	1462	1455	DeepSeek V4 Pro 0813
LMArena WebDev: React	1588	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena WebDev: HTML	1566	1350	DeepSeek V4 Pro 0813
Neither model has a result on the other 14 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10

Intelligence benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
AA Intelligence Index	36.0	18.5	DeepSeek V4 Pro 0813
Epoch Capabilities Index	155.6	Not measured	Only DeepSeek V4 Pro 0813 measured

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared

Agentic work benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
AA Agentic Index	41.3	Not measured	Only DeepSeek V4 Pro 0813 measured
Design Arena: agents building full-stack apps	Not measured	1029	Only GLM 4.6 measured
Design Arena: agents building mobile apps	Not measured	1096	Only GLM 4.6 measured
Design Arena: agents building Android apps	Not measured	1084	Only GLM 4.6 measured
Design Arena: agents building Godot games	Not measured	1180	Only GLM 4.6 measured
SREBench (Vals AI)	1.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)	50.4%	Not measured	Only DeepSeek V4 Pro 0813 measured
Tax Agent Bench (Vals AI)	26.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
Legal Research Bench (Vals AI)	40.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
Harvey's Legal Agent Benchmark (Vals AI)	10.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)	52.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench-Science (Vals AI)	4.3%	Not measured	Only DeepSeek V4 Pro 0813 measured
τ²-Bench Telecom	Not measured	76.9%	Only GLM 4.6 measured
APEX-Agents	47.3%	Not measured	Only DeepSeek V4 Pro 0813 measured
Berkeley Function Calling Leaderboard (BFCL)	Not measured	72.4%	Only GLM 4.6 measured
BrowseComp-Plus	Not measured	48.2%	Only GLM 4.6 measured
Neither model has a result on the other 25 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index60

Reasoning benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
GPQA Diamond	92.4%	74.5%	DeepSeek V4 Pro 0813
GPQA Diamond (Artificial Analysis run)	92.8%	78.0%	DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)	41.0%	14.5%	DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)	91.7%	Not measured	Only DeepSeek V4 Pro 0813 measured
ARC-AGI	90.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
ARC-AGI-2	61.3%	Not measured	Only DeepSeek V4 Pro 0813 measured
Chess puzzles	46.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
Mystery game puzzles	43.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena Text: hard prompts	1458	1440	DeepSeek V4 Pro 0813
LMArena Text: expert	1459	1432	DeepSeek V4 Pro 0813
LMArena Text: hard prompts in English	1463	1445	DeepSeek V4 Pro 0813
Kagi LLM Benchmark	Not measured	45.7%	Only GLM 4.6 measured
Neither model has a result on the other 10 boards here

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

Math benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
AIME	Not measured	92.7%	Only GLM 4.6 measured
MGSM (Vals AI)	Not measured	89.8%	Only GLM 4.6 measured
AA Math Index	Not measured	86.0	Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)	Not measured	86.0%	Only GLM 4.6 measured
OTIS Mock AIME	98.6%	Not measured	Only DeepSeek V4 Pro 0813 measured
FrontierMath, tiers 1 to 3	64.6%	Not measured	Only DeepSeek V4 Pro 0813 measured
FrontierMath, tier 4	26.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
ProofBench	50.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena Text: math	1441	1432	DeepSeek V4 Pro 0813
LMArena Text: mathematical work	1443	1447	GLM 4.6
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index71

Knowledge benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
MMLU Pro	87.0%	82.2%	DeepSeek V4 Pro 0813
LegalBench (Vals AI)	82.4%	79.6%	DeepSeek V4 Pro 0813
CorpFin (Vals AI)	65.4%	56.8%	DeepSeek V4 Pro 0813
TaxEval (Vals AI)	73.1%	66.2%	DeepSeek V4 Pro 0813
MedQA (Vals AI)	Not measured	92.2%	Only GLM 4.6 measured
MedCode (Vals AI)	42.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
MMLU Pro (Artificial Analysis run)	Not measured	82.9%	Only GLM 4.6 measured
SimpleQA Verified	52.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena Text: science	1457	1456	DeepSeek V4 Pro 0813
LMArena Text: medicine and healthcare	1446	1455	GLM 4.6
LMArena Text: legal and government	1459	1448	DeepSeek V4 Pro 0813
LMArena Text: business and finance	1442	1416	DeepSeek V4 Pro 0813
Neither model has a result on the other 6 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared

Web design benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
Design Arena: websites	Not measured	1174	Only GLM 4.6 measured
Design Arena: UI components	Not measured	1145	Only GLM 4.6 measured
Design Arena: game dev	Not measured	1150	Only GLM 4.6 measured
Design Arena: data viz	Not measured	1161	Only GLM 4.6 measured
Design Arena: 3D	Not measured	1128	Only GLM 4.6 measured
Design Arena: all code categories	Not measured	1165	Only GLM 4.6 measured
Design Arena: SVG	Not measured	1108	Only GLM 4.6 measured
Neither model has a result on the other 2 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index123

General benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	Leader
Vals Index	53.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
MedScribe (Vals AI)	80.2%	Not measured	Only DeepSeek V4 Pro 0813 measured
IFBench	Not measured	43.4%	Only GLM 4.6 measured
Long context reasoning (AA-LCR)	80.3%	54.0%	DeepSeek V4 Pro 0813
DTBench	93.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMCA	45.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena Text	1446	1440	DeepSeek V4 Pro 0813
LMArena Text: instruction following	1448	1410	DeepSeek V4 Pro 0813
LMArena Text: creative writing	1439	1412	DeepSeek V4 Pro 0813
LMArena Text: English	1457	1449	DeepSeek V4 Pro 0813
LMArena Text: non-English	1431	1426	DeepSeek V4 Pro 0813
LMArena Text: Chinese	1481	1499	GLM 4.6
LMArena Text: German	Not measured	1447	Only GLM 4.6 measured
LMArena Text: Japanese	Not measured	1393	Only GLM 4.6 measured
LMArena Text: Korean	1449	1400	DeepSeek V4 Pro 0813
LMArena Text: French	1446	1459	GLM 4.6
LMArena Text: Spanish	1435	1436	GLM 4.6
LMArena Text: Russian	1448	1418	DeepSeek V4 Pro 0813
LMArena Text: Polish	Not measured	1447	Only GLM 4.6 measured
LMArena Text: multi-turn	1454	1427	DeepSeek V4 Pro 0813
LMArena Text: longer queries	1458	1422	DeepSeek V4 Pro 0813
LMArena Text: writing and language	1443	1415	DeepSeek V4 Pro 0813
LMArena Text: entertainment and media	1424	1409	DeepSeek V4 Pro 0813
Neither model has a result on the other 23 boards here

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

Image generation benchmarks for DeepSeek V4 Pro 0813 and GLM 4.6
Benchmark	DeepSeek V4 Pro 0813	GLM 4.6	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 Pro 0813$0.0016Fits in one request

GLM 4.6$0.0017Fits in one request

DeepSeek V4 Pro 0813 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits 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 0813$0.152Fits 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 0813 and GLM 4.6
Specification	DeepSeek V4 Pro 0813	Z.ai GLM 4.6
Maker	DeepSeek	Z.ai
Weights	Open weights	Open weights
Released	August 12, 2026	September 30, 2025
Context window	1.05M	205K
Input $/Mtok	$0.66	$0.60
Output $/Mtok	$1.98	$2.20
Coding index	56.1	8.8
Independent measurements behind it	5	2
Cost per solved task	$0.10	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than GLM 4.6 for coding?

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for work measured by LMArena Text: mathematical work or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, DeepSeek V4 Pro 0813 or GLM 4.6?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for DeepSeek V4 Pro 0813 only.

Which has the bigger context window, DeepSeek V4 Pro 0813 or GLM 4.6?

DeepSeek V4 Pro 0813, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Pro 0813 vs GLM 4.6 comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813'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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DeepSeek V4 Pro 0813 or GLM 4.6: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task