Claude Opus 4.8 vs DeepSeek V4 Pro 0813

Claude Opus 4.8 leads DeepSeek V4 Pro 0813 on coding, 65.0 to 56.1 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; 71 benchmarks have a result for both.

Replace Claude Opus 4.8 Replace DeepSeek V4 Pro 0813

Claude Opus 4.8Anthropic

Coding: 65.0
Overall: 69.8
Output $/M: $25.00

DeepSeek V4 Pro 0813DeepSeek

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

vs boards won of 71 shared, 2 tied

Claude Opus 4.8 or DeepSeek V4 Pro 0813: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813.

Pick DeepSeek V4 Pro 0813 for output tokens 12.6x cheaper ($1.98 vs $25.00 per million) and a lower cost per solved task ($0.10 against $2.17).

Model AClaude Opus 4.8Anthropic65.0/1006 independent benchmarks$2.17 per solved task Model BDeepSeek V4 Pro 0813DeepSeek56.1/1005 independent benchmarks$0.10 per solved task

71597

Shared results: 71
Claude Opus 4.8 only: 59
DeepSeek V4 Pro 0813 only: 7
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.

Coding
Vibe Coding Index, six public coding benchmarks
Claude Opus 4.8
Claude Opus 4.8 scores 65.0 against 56.1.
6 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Opus 4.8
Claude Opus 4.8 leads, 41.8 against 36.0.
Same board, both measured
Agentic work
AA Agentic Index
Claude Opus 4.8
Claude Opus 4.8 leads, 41.9 against 41.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Tied at 92.4%.
Same board, both measured
Knowledge
MMLU Pro
Claude Opus 4.8
Claude Opus 4.8 leads, 89.6% against 87.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Claude Opus 4.8 has a Design Arena: websites result, 1258.
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 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
Claude Opus 4.8 $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 4.8 $2.17, DeepSeek V4 Pro 0813 $0.10.
Published attempt cost and pass rate

At a glance

Coding index: Claude Opus 4.8 65.0 from 6 benchmarks, DeepSeek V4 Pro 0813 56.1 from 5 benchmarks.
Widest category: Math, 13.4 points apart on average over 6 shared benchmarks.
Widest single gap: FrontierMath, tier 4: Claude Opus 4.8 56.1% against DeepSeek V4 Pro 0813 26.8%, 29.3 points apart on a 0 to 100 scale.
Output price: Claude Opus 4.8 $25.00 against DeepSeek V4 Pro 0813 $1.98 per million output tokens, 12.6x apart.
Context window: Claude Opus 4.8 takes 1M 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 4.8	DeepSeek V4 Pro 0813	Ties
Coding	13	4
Intelligence	2	0
Agentic work	6	0	1 tie
Reasoning	7	3	1 tie
Math	5	1
Knowledge	10	0
General	16	2
All shared boards	59	10	2 ties

CodingLike-for-likeSix of these boards feed the Vibe Coding Index134

Coding benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
LiveBench coding	77.3%	Not measured	Only Claude Opus 4.8 measured
LMArena WebDev	1556	1582	DeepSeek V4 Pro 0813
AA Coding Index	74.3	68.8	Claude Opus 4.8
LiveCodeBench (Vals AI)	87.8%	87.5%	Claude Opus 4.8
SWE-bench Verified (Vals AI)	88.6%	96.4%	DeepSeek V4 Pro 0813
Terminal-Bench 4 (Vals AI)	23.2%	14.1%	Claude Opus 4.8
Vibe Code Bench (Vals AI)	82.7%	82.3%	Claude Opus 4.8
Code migration (Vals AI)	47.3%	41.5%	Claude Opus 4.8
ProgramBench (Vals AI)	1.0%	0.0%	Claude Opus 4.8
IOI (Vals AI)	Not measured	51.6%	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)	71.9%	54.7%	Claude Opus 4.8
Vibe Code Bench 1-100 (Vals AI)	Not measured	17.5%	Only DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)	59.2%	53.8%	Claude Opus 4.8
CyberBench (Vals AI)	Not measured	72.9%	Only DeepSeek V4 Pro 0813 measured
SciCode	54.4%	51.0%	Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)	58.3%	Not measured	Only Claude Opus 4.8 measured
FrontierCode	46.5%	28.5%	Claude Opus 4.8
GSO-Bench	47.1%	Not measured	Only Claude Opus 4.8 measured
WeirdML	82.9%	66.2%	Claude Opus 4.8
ALE-Bench	Not measured	1403.2	Only DeepSeek V4 Pro 0813 measured
LMArena Text: coding	1490	1469	Claude Opus 4.8
LMArena Text: software and IT	1488	1462	Claude Opus 4.8
LMArena WebDev: React	1557	1588	DeepSeek V4 Pro 0813
LMArena WebDev: HTML	1543	1566	DeepSeek V4 Pro 0813
SciCode	12.3%	Not measured	Only Claude Opus 4.8 measured
Neither model has a result on the other 14 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
AA Intelligence Index	41.8	36.0	Claude Opus 4.8
Epoch Capabilities Index	159.0	155.6	Claude Opus 4.8

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

Agentic work benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
AA Agentic Index	41.9	41.3	Claude Opus 4.8
Design Arena: agents building web apps	1233	Not measured	Only Claude Opus 4.8 measured
Design Arena: agents building full-stack apps	1249	Not measured	Only Claude Opus 4.8 measured
Design Arena: agents building mobile apps	1222	Not measured	Only Claude Opus 4.8 measured
Design Arena: agents building Android apps	1233	Not measured	Only Claude Opus 4.8 measured
Design Arena: agents building Godot games	1231	Not measured	Only Claude Opus 4.8 measured
Design Arena: agents building games	1239	Not measured	Only Claude Opus 4.8 measured
Design Arena: HTML slides	1171	Not measured	Only Claude Opus 4.8 measured
Design Arena: PowerPoint slides	1202	Not measured	Only Claude Opus 4.8 measured
Design Arena: spreadsheets	1303	Not measured	Only Claude Opus 4.8 measured
LiveBench research	81.8%	Not measured	Only Claude Opus 4.8 measured
LiveBench browser	96.0%	Not measured	Only Claude Opus 4.8 measured
LiveBench long agentic	48.3%	Not measured	Only Claude Opus 4.8 measured
SREBench (Vals AI)	Not measured	1.9%	Only DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)	53.9%	50.4%	Claude Opus 4.8
Tax Agent Bench (Vals AI)	30.0%	26.8%	Claude Opus 4.8
Legal Research Bench (Vals AI)	43.8%	40.9%	Claude Opus 4.8
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	10.8%	Only DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)	69.4%	52.8%	Claude Opus 4.8
Terminal-Bench-Science (Vals AI)	4.3%	4.3%	Tie
Time Horizon Index (Vals AI)	11.8%	Not measured	Only Claude Opus 4.8 measured
τ²-Bench Telecom	94.4%	Not measured	Only Claude Opus 4.8 measured
APEX-Agents	48.9%	47.3%	Claude Opus 4.8
Remote Labor Index	8.3%	Not measured	Only Claude Opus 4.8 measured
OSWorld 2.0	20.6%	Not measured	Only Claude Opus 4.8 measured
DeepResearch Bench	50.2%	Not measured	Only Claude Opus 4.8 measured
PostTrainBench	33.8%	Not measured	Only Claude Opus 4.8 measured
Vending-Bench 2	$5,787	Not measured	Only Claude Opus 4.8 measured
LMArena Search	1204	Not measured	Only Claude Opus 4.8 measured
Neither model has a result on the other 12 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index73

Reasoning benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
GPQA Diamond	92.4%	92.4%	Tie
LiveBench reasoning	89.2%	Not measured	Only Claude Opus 4.8 measured
MMMU Pro (Vals AI)	86.6%	Not measured	Only Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)	92.0%	92.8%	DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)	48.7%	41.0%	Claude Opus 4.8
GPQA Diamond (Epoch AI run)	91.0%	91.7%	DeepSeek V4 Pro 0813
ARC-AGI	92.5%	90.5%	Claude Opus 4.8
ARC-AGI-2	72.1%	61.3%	Claude Opus 4.8
SimpleBench	64.8%	Not measured	Only Claude Opus 4.8 measured
Chess puzzles	52.0%	46.0%	Claude Opus 4.8
Mystery game puzzles	36.0%	43.0%	DeepSeek V4 Pro 0813
EBR-bench	28.6%	Not measured	Only Claude Opus 4.8 measured
LMArena Text: hard prompts	1482	1458	Claude Opus 4.8
LMArena Text: expert	1503	1459	Claude Opus 4.8
LMArena Text: hard prompts in English	1487	1463	Claude Opus 4.8
LMArena Vision: diagrams	1315	Not measured	Only Claude Opus 4.8 measured
LMArena Vision: homework	1337	Not measured	Only Claude Opus 4.8 measured
Kagi LLM Benchmark	88.8%	Not measured	Only Claude Opus 4.8 measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index51

Math benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
OTIS Mock AIME	98.3%	98.6%	DeepSeek V4 Pro 0813
FrontierMath, tiers 1 to 3	80.0%	64.6%	Claude Opus 4.8
FrontierMath, tier 4	56.1%	26.8%	Claude Opus 4.8
ProofBench	69.0%	50.0%	Claude Opus 4.8
LMArena Text: math	1486	1441	Claude Opus 4.8
LMArena Text: mathematical work	1497	1443	Claude Opus 4.8
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index100

Knowledge benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
MMLU Pro	89.6%	87.0%	Claude Opus 4.8
LegalBench (Vals AI)	83.6%	82.4%	Claude Opus 4.8
CorpFin (Vals AI)	66.7%	65.4%	Claude Opus 4.8
TaxEval (Vals AI)	75.6%	73.1%	Claude Opus 4.8
MortgageTax (Vals AI)	69.9%	Not measured	Only Claude Opus 4.8 measured
MedCode (Vals AI)	53.2%	42.5%	Claude Opus 4.8
SimpleQA Verified	53.0%	52.9%	Claude Opus 4.8
LMArena Text: science	1477	1457	Claude Opus 4.8
LMArena Text: medicine and healthcare	1464	1446	Claude Opus 4.8
LMArena Text: legal and government	1477	1459	Claude Opus 4.8
LMArena Text: business and finance	1458	1442	Claude Opus 4.8
FACTS Benchmark Suite	53.5%	Not measured	Only Claude Opus 4.8 measured
Neither model has a result on the other 6 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared

Web design benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
Design Arena: websites	1258	Not measured	Only Claude Opus 4.8 measured
Design Arena: UI components	1255	Not measured	Only Claude Opus 4.8 measured
Design Arena: game dev	1264	Not measured	Only Claude Opus 4.8 measured
Design Arena: data viz	1240	Not measured	Only Claude Opus 4.8 measured
Design Arena: 3D	1222	Not measured	Only Claude Opus 4.8 measured
Design Arena: all code categories	1255	Not measured	Only Claude Opus 4.8 measured
Design Arena: SVG	1195	Not measured	Only Claude Opus 4.8 measured
Design Arena: ASCII art	1277	Not measured	Only Claude Opus 4.8 measured
LiveBench design	78.8%	Not measured	Only Claude Opus 4.8 measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index162

General benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	DeepSeek V4 Pro 0813	Leader
Vals Index	Not measured	53.0%	Only DeepSeek V4 Pro 0813 measured
LiveBench data analysis	66.0%	Not measured	Only Claude Opus 4.8 measured
Public Benefits Bench (Vals AI)	68.1%	Not measured	Only Claude Opus 4.8 measured
SAGE (Vals AI)	54.8%	Not measured	Only Claude Opus 4.8 measured
MedScribe (Vals AI)	85.8%	80.2%	Claude Opus 4.8
Vals Multimodal Index	70.9%	Not measured	Only Claude Opus 4.8 measured
IFBench	62.2%	Not measured	Only Claude Opus 4.8 measured
Long context reasoning (AA-LCR)	77.7%	80.3%	DeepSeek V4 Pro 0813
DTBench	94.9%	93.9%	Claude Opus 4.8
LMCA	57.5%	45.5%	Claude Opus 4.8
Surface Evolver Bench	87.5%	Not measured	Only Claude Opus 4.8 measured
Furniture assembly	42.5%	Not measured	Only Claude Opus 4.8 measured
LMArena Text	1461	1446	Claude Opus 4.8
LMArena Text: instruction following	1476	1448	Claude Opus 4.8
LMArena Text: creative writing	1454	1439	Claude Opus 4.8
LMArena Vision	1294	Not measured	Only Claude Opus 4.8 measured
LMArena Text: English	1468	1457	Claude Opus 4.8
LMArena Text: non-English	1450	1431	Claude Opus 4.8
LMArena Text: Chinese	1506	1481	Claude Opus 4.8
LMArena Text: German	1472	Not measured	Only Claude Opus 4.8 measured
LMArena Text: Japanese	1442	Not measured	Only Claude Opus 4.8 measured
LMArena Text: Korean	1431	1449	DeepSeek V4 Pro 0813
LMArena Text: French	1481	1446	Claude Opus 4.8
LMArena Text: Spanish	1465	1435	Claude Opus 4.8
LMArena Text: Russian	1474	1448	Claude Opus 4.8
LMArena Text: Polish	1459	Not measured	Only Claude Opus 4.8 measured
LMArena Text: multi-turn	1476	1454	Claude Opus 4.8
LMArena Text: longer queries	1483	1458	Claude Opus 4.8
LMArena Text: writing and language	1461	1443	Claude Opus 4.8
LMArena Text: entertainment and media	1440	1424	Claude Opus 4.8
LMArena Vision: English	1293	Not measured	Only Claude Opus 4.8 measured
LMArena Vision: Chinese	1346	Not measured	Only Claude Opus 4.8 measured
LMArena Vision: reading text	1303	Not measured	Only Claude Opus 4.8 measured
LMArena Vision: humor	1282	Not measured	Only Claude Opus 4.8 measured
LMArena Vision: creative writing	1301	Not measured	Only Claude Opus 4.8 measured
LMArena Document	1475	Not measured	Only Claude Opus 4.8 measured
Neither model has a result on the other 10 boards here

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

Image generation benchmarks for Claude Opus 4.8 and DeepSeek V4 Pro 0813
Benchmark	Claude Opus 4.8	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 4.8$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 4.8$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 4.8$1.25Fits in one request

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 4.8 and DeepSeek V4 Pro 0813
Specification	Anthropic Claude Opus 4.8	DeepSeek V4 Pro 0813
Maker	Anthropic	DeepSeek
Weights	No public weights listed	Open weights
Released	May 27, 2026	August 12, 2026
Context window	1M	1.05M
Input $/Mtok	$5.00	$0.66
Output $/Mtok	$25.00	$1.98
Coding index	65.0	56.1
Independent measurements behind it	6	5
Cost per solved task	$2.17	$0.10
Source	OpenRouter listing	OpenRouter listing

Questions

Is Claude Opus 4.8 better than DeepSeek V4 Pro 0813 for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 for output tokens 12.6x cheaper ($1.98 vs $25.00 per million) and a lower cost per solved task ($0.10 against $2.17).

Which is cheaper, Claude Opus 4.8 or DeepSeek V4 Pro 0813?

Claude Opus 4.8 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 4.8 costs $2.17 and DeepSeek V4 Pro 0813 $0.10.

Which has the bigger context window, Claude Opus 4.8 or DeepSeek V4 Pro 0813?

DeepSeek V4 Pro 0813, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs DeepSeek V4 Pro 0813 comparison based on?

71 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.8's coding index rests on 6 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.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/claude-opus-4-8-vs-deepseek-v4-pro-0813" title="Claude Opus 4.8 vs DeepSeek V4 Pro 0813, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/claude-opus-4-8-vs-deepseek-v4-pro-0813">LLMBenchmark.ai, Claude Opus 4.8 vs DeepSeek V4 Pro 0813</a></p>

Claude Opus 4.8 or DeepSeek V4 Pro 0813: 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