Claude Opus 4.5 vs DeepSeek V4 Pro 0813

DeepSeek V4 Pro 0813 leads Claude Opus 4.5 on coding, 56.1 to 44.0 on the Vibe Coding Index, and DeepSeek V4 Pro 0813 costs 12.6x less per output token ($1.98 vs $25.00 per million). Updated October 22, 2026; 56 benchmarks have a result for both.

Replace Claude Opus 4.5 Replace DeepSeek V4 Pro 0813

Claude Opus 4.5Anthropic

Coding: 44.0
Overall: 55.7
Output $/M: $25.00

DeepSeek V4 Pro 0813DeepSeek

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

vs boards won of 56 shared

Claude Opus 4.5 or DeepSeek V4 Pro 0813: which to pick

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 44.0 for Claude Opus 4.5.

Pick Claude Opus 4.5 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AClaude Opus 4.5Anthropic44.0/1003 independent benchmarks$1.37 per solved task Model BDeepSeek V4 Pro 0813DeepSeek56.1/1005 independent benchmarks$0.10 per solved task

565222

Shared results: 56
Claude Opus 4.5 only: 52
DeepSeek V4 Pro 0813 only: 22
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 44.0.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 29.1.
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 85.9%.
Same board, both measured
Math
AIME
No call
Only Claude Opus 4.5 has a AIME result, 95.4%.
Directional only
Knowledge
MMLU Pro
Claude Opus 4.5
Claude Opus 4.5 leads, 87.3% against 87.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Claude Opus 4.5 has a Design Arena: websites result, 1247.
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 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
Claude Opus 4.5 $0.018, DeepSeek V4 Pro 0813 $0.0016 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0813
Claude Opus 4.5 $1.37, DeepSeek V4 Pro 0813 $0.10.
Published attempt cost and pass rate

At a glance

Coding index: Claude Opus 4.5 44.0 from 3 benchmarks, DeepSeek V4 Pro 0813 56.1 from 5 benchmarks.
Widest category: Coding, 15.3 points apart on average over 9 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): Claude Opus 4.5 20.6% against DeepSeek V4 Pro 0813 82.3%, 61.7 points apart on a 0 to 100 scale.
Output price: Claude Opus 4.5 $25.00 against DeepSeek V4 Pro 0813 $1.98 per million output tokens, 12.6x apart.
Context window: Claude Opus 4.5 takes 200K tokens, DeepSeek V4 Pro 0813 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
Category	Claude Opus 4.5	DeepSeek V4 Pro 0813
Coding	2	7
Intelligence	0	2
Reasoning	3	8
Math	2	4
Knowledge	5	5
General	12	6
All shared boards	24	32

CodingLike-for-likeSix of these boards feed the Vibe Coding Index27

Coding benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
SWE-bench Verified	79.2%	Not measured	Only Claude Opus 4.5 measured
SWE-bench (full test set)	52.6%	Not measured	Only Claude Opus 4.5 measured
SWE-bench Multilingual	70.7%	Not measured	Only Claude Opus 4.5 measured
LMArena WebDev	1494	1582	DeepSeek V4 Pro 0813
AA Coding Index	Not measured	68.8	Only DeepSeek V4 Pro 0813 measured
LiveCodeBench (Vals AI)	83.7%	87.5%	DeepSeek V4 Pro 0813
SWE-bench Verified (Vals AI)	76.4%	96.4%	DeepSeek V4 Pro 0813
Terminal-Bench 4 (Vals AI)	Not measured	14.1%	Only DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)	20.6%	82.3%	DeepSeek V4 Pro 0813
Code migration (Vals AI)	Not measured	41.5%	Only DeepSeek V4 Pro 0813 measured
ProgramBench (Vals AI)	Not measured	0.0%	Only DeepSeek V4 Pro 0813 measured
IOI (Vals AI)	Not measured	51.6%	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)	Not measured	54.7%	Only DeepSeek V4 Pro 0813 measured
Vibe Code Bench 1-100 (Vals AI)	Not measured	17.5%	Only DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)	Not measured	53.8%	Only DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)	Not measured	72.9%	Only DeepSeek V4 Pro 0813 measured
LiveCodeBench (Artificial Analysis run)	87.1%	Not measured	Only Claude Opus 4.5 measured
SciCode	Not measured	51.0%	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench Hard (Artificial Analysis run)	47.0%	Not measured	Only Claude Opus 4.5 measured
Terminal-Bench	63.1%	Not measured	Only Claude Opus 4.5 measured
FrontierCode	Not measured	28.5%	Only DeepSeek V4 Pro 0813 measured
GSO-Bench	26.5%	Not measured	Only Claude Opus 4.5 measured
WeirdML	63.7%	66.2%	DeepSeek V4 Pro 0813
Cybench	82.0%	Not measured	Only Claude Opus 4.5 measured
ALE-Bench	Not measured	1403.2	Only DeepSeek V4 Pro 0813 measured
LMArena Text: coding	1503	1469	Claude Opus 4.5
LMArena Text: software and IT	1483	1462	Claude Opus 4.5
LMArena WebDev: React	1478	1588	DeepSeek V4 Pro 0813
LMArena WebDev: HTML	1510	1566	DeepSeek V4 Pro 0813
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 Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
AA Intelligence Index	29.1	36.0	DeepSeek V4 Pro 0813
Epoch Capabilities Index	150.1	155.6	DeepSeek V4 Pro 0813

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared

Agentic work benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
AA Agentic Index	Not measured	41.3	Only DeepSeek V4 Pro 0813 measured
Design Arena: agents building web apps	1159	Not measured	Only Claude Opus 4.5 measured
Design Arena: agents building full-stack apps	1156	Not measured	Only Claude Opus 4.5 measured
Design Arena: agents building mobile apps	1189	Not measured	Only Claude Opus 4.5 measured
Design Arena: agents building Android apps	1176	Not measured	Only Claude Opus 4.5 measured
SREBench (Vals AI)	Not measured	1.9%	Only DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)	Not measured	50.4%	Only DeepSeek V4 Pro 0813 measured
Tax Agent Bench (Vals AI)	Not measured	26.8%	Only DeepSeek V4 Pro 0813 measured
Legal Research Bench (Vals AI)	Not measured	40.9%	Only DeepSeek V4 Pro 0813 measured
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	10.8%	Only DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)	Not measured	52.8%	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench-Science (Vals AI)	Not measured	4.3%	Only DeepSeek V4 Pro 0813 measured
τ²-Bench Telecom	89.5%	Not measured	Only Claude Opus 4.5 measured
APEX-Agents	Not measured	47.3%	Only DeepSeek V4 Pro 0813 measured
METR time horizons	75.0%	Not measured	Only Claude Opus 4.5 measured
Remote Labor Index	3.8%	Not measured	Only Claude Opus 4.5 measured
GDPval	45.5%	Not measured	Only Claude Opus 4.5 measured
BALROG	43.5%	Not measured	Only Claude Opus 4.5 measured
DeepResearch Bench	54.8%	Not measured	Only Claude Opus 4.5 measured
OSWorld	66.3%	Not measured	Only Claude Opus 4.5 measured
Vending-Bench 2	$4,967	Not measured	Only Claude Opus 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)	77.5%	Not measured	Only Claude Opus 4.5 measured
Neither model has a result on the other 19 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index38

Reasoning benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
GPQA Diamond	85.9%	92.4%	DeepSeek V4 Pro 0813
MMMU Pro (Vals AI)	83.0%	Not measured	Only Claude Opus 4.5 measured
GPQA Diamond (Artificial Analysis run)	86.6%	92.8%	DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)	30.1%	41.0%	DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)	86.0%	91.7%	DeepSeek V4 Pro 0813
ARC-AGI	80.0%	90.5%	DeepSeek V4 Pro 0813
ARC-AGI-2	37.6%	61.3%	DeepSeek V4 Pro 0813
SimpleBench	62.0%	Not measured	Only Claude Opus 4.5 measured
Chess puzzles	14.0%	46.0%	DeepSeek V4 Pro 0813
Mystery game puzzles	22.0%	43.0%	DeepSeek V4 Pro 0813
EBR-bench	14.3%	Not measured	Only Claude Opus 4.5 measured
VPCT	40.0%	Not measured	Only Claude Opus 4.5 measured
LMArena Text: hard prompts	1476	1458	Claude Opus 4.5
LMArena Text: expert	1487	1459	Claude Opus 4.5
LMArena Text: hard prompts in English	1482	1463	Claude Opus 4.5
Kagi LLM Benchmark	80.2%	Not measured	Only Claude Opus 4.5 measured
Neither model has a result on the other 6 boards here

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

Math benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
AIME	95.4%	Not measured	Only Claude Opus 4.5 measured
MGSM (Vals AI)	95.2%	Not measured	Only Claude Opus 4.5 measured
AA Math Index	91.3	Not measured	Only Claude Opus 4.5 measured
AIME 2025 (Artificial Analysis run)	91.3%	Not measured	Only Claude Opus 4.5 measured
OTIS Mock AIME	86.1%	98.6%	DeepSeek V4 Pro 0813
FrontierMath, tiers 1 to 3	34.4%	64.6%	DeepSeek V4 Pro 0813
FrontierMath, tier 4	4.9%	26.8%	DeepSeek V4 Pro 0813
ProofBench	36.0%	50.0%	DeepSeek V4 Pro 0813
LMArena Text: math	1463	1441	Claude Opus 4.5
LMArena Text: mathematical work	1468	1443	Claude Opus 4.5
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index55

Knowledge benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
MMLU Pro	87.3%	87.0%	Claude Opus 4.5
LegalBench (Vals AI)	84.6%	82.4%	Claude Opus 4.5
CaseLaw (Vals AI)	62.6%	Not measured	Only Claude Opus 4.5 measured
CorpFin (Vals AI)	65.1%	65.4%	DeepSeek V4 Pro 0813
TaxEval (Vals AI)	74.9%	73.1%	Claude Opus 4.5
MortgageTax (Vals AI)	68.7%	Not measured	Only Claude Opus 4.5 measured
MedQA (Vals AI)	95.9%	Not measured	Only Claude Opus 4.5 measured
MedCode (Vals AI)	49.2%	42.5%	Claude Opus 4.5
MMLU Pro (Artificial Analysis run)	89.5%	Not measured	Only Claude Opus 4.5 measured
SimpleQA Verified	45.7%	52.9%	DeepSeek V4 Pro 0813
GeoBench	75.0%	Not measured	Only Claude Opus 4.5 measured
LMArena Text: science	1454	1457	DeepSeek V4 Pro 0813
LMArena Text: medicine and healthcare	1444	1446	DeepSeek V4 Pro 0813
LMArena Text: legal and government	1459	1459	DeepSeek V4 Pro 0813
LMArena Text: business and finance	1448	1442	Claude Opus 4.5
FACTS Benchmark Suite	43.9%	Not measured	Only Claude Opus 4.5 measured
Neither model has a result on the other 2 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared

Web design benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
Design Arena: websites	1247	Not measured	Only Claude Opus 4.5 measured
Design Arena: UI components	1235	Not measured	Only Claude Opus 4.5 measured
Design Arena: game dev	1228	Not measured	Only Claude Opus 4.5 measured
Design Arena: data viz	1243	Not measured	Only Claude Opus 4.5 measured
Design Arena: 3D	1213	Not measured	Only Claude Opus 4.5 measured
Design Arena: all code categories	1242	Not measured	Only Claude Opus 4.5 measured
Design Arena: SVG	1180	Not measured	Only Claude Opus 4.5 measured
Design Arena: ASCII art	1190	Not measured	Only Claude Opus 4.5 measured
Neither model has a result on the other 1 board here

GeneralLike-for-likePublic boards, shown as published, kept out of the index126

General benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	Leader
Vals Index	Not measured	53.0%	Only DeepSeek V4 Pro 0813 measured
SAGE (Vals AI)	52.1%	Not measured	Only Claude Opus 4.5 measured
MedScribe (Vals AI)	85.3%	80.2%	Claude Opus 4.5
IFBench	58.0%	Not measured	Only Claude Opus 4.5 measured
Long context reasoning (AA-LCR)	77.3%	80.3%	DeepSeek V4 Pro 0813
DTBench	89.9%	93.9%	DeepSeek V4 Pro 0813
LMCA	44.5%	45.5%	DeepSeek V4 Pro 0813
CL-bench	21.1%	Not measured	Only Claude Opus 4.5 measured
Furniture assembly	28.3%	Not measured	Only Claude Opus 4.5 measured
LMArena Text	1451	1446	Claude Opus 4.5
LMArena Text: instruction following	1478	1448	Claude Opus 4.5
LMArena Text: creative writing	1445	1439	Claude Opus 4.5
LMArena Text: English	1461	1457	Claude Opus 4.5
LMArena Text: non-English	1438	1431	Claude Opus 4.5
LMArena Text: Chinese	1470	1481	DeepSeek V4 Pro 0813
LMArena Text: German	1449	Not measured	Only Claude Opus 4.5 measured
LMArena Text: Japanese	1417	Not measured	Only Claude Opus 4.5 measured
LMArena Text: Korean	1424	1449	DeepSeek V4 Pro 0813
LMArena Text: French	1471	1446	Claude Opus 4.5
LMArena Text: Spanish	1457	1435	Claude Opus 4.5
LMArena Text: Russian	1447	1448	DeepSeek V4 Pro 0813
LMArena Text: Polish	1439	Not measured	Only Claude Opus 4.5 measured
LMArena Text: multi-turn	1466	1454	Claude Opus 4.5
LMArena Text: longer queries	1479	1458	Claude Opus 4.5
LMArena Text: writing and language	1452	1443	Claude Opus 4.5
LMArena Text: entertainment and media	1434	1424	Claude Opus 4.5
LMArena Document	1462	Not measured	Only Claude Opus 4.5 measured
Neither model has a result on the other 19 boards here

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

Image generation benchmarks for Claude Opus 4.5 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.5	DeepSeek V4 Pro 0813	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

Claude Opus 4.5$0.018Fits in one request

DeepSeek V4 Pro 0813$0.0016Fits in one request

DeepSeek V4 Pro 0813 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.5$0.325Fits in one request

DeepSeek V4 Pro 0813$0.039Fits in one request

DeepSeek V4 Pro 0813 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.5$1.25Exceeds the context window

DeepSeek V4 Pro 0813$0.152Fits in one request

DeepSeek V4 Pro 0813 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 Claude Opus 4.5 and DeepSeek V4 Pro 0813
Specification	Anthropic Claude Opus 4.5	DeepSeek V4 Pro 0813
Maker	Anthropic	DeepSeek
Weights	No public weights listed	Open weights
Released	November 24, 2025	August 12, 2026
Context window	200K	1.05M
Input $/Mtok	$5.00	$0.66
Output $/Mtok	$25.00	$1.98
Coding index	44.0	56.1
Independent measurements behind it	3	5
Cost per solved task	$1.37	$0.10
Source	OpenRouter listing	OpenRouter listing

Questions

Is Claude Opus 4.5 better than DeepSeek V4 Pro 0813 for coding?

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 44.0 for Claude Opus 4.5. Pick Claude Opus 4.5 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Claude Opus 4.5 or DeepSeek V4 Pro 0813?

Claude Opus 4.5 costs $5.00 per million input tokens and $25.00 per million output tokens; DeepSeek V4 Pro 0813 costs $0.66 and $1.98. Per solved SWE-bench Verified task, Claude Opus 4.5 costs $1.37 and DeepSeek V4 Pro 0813 $0.10.

Which has the bigger context window, Claude Opus 4.5 or DeepSeek V4 Pro 0813?

DeepSeek V4 Pro 0813, with 1.05M tokens against 200K.

How many benchmarks is the Claude Opus 4.5 vs DeepSeek V4 Pro 0813 comparison based on?

56 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.5's coding index rests on 3 independent benchmarks and DeepSeek V4 Pro 0813's on 5. Where only one model has a result, the page says so instead of naming a winner.

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Claude Opus 4.5 or DeepSeek V4 Pro 0813: 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

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next