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Claude Opus 4.8 vs DeepSeek V4.1 Flash

Claude Opus 4.8 leads DeepSeek V4.1 Flash on coding, 65.0 to 62.5 on the Vibe Coding Index, and DeepSeek V4.1 Flash costs 29.8x less per output token ($0.84 vs $25.00 per million). Updated October 22, 2026; 91 benchmarks have a result for both.

Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
59
DeepSeek V4.1 FlashDeepSeek
Coding
62.5
Overall
62.4
Output $/M
$0.84
31
vs boards won of 91 shared, 1 tied

Claude Opus 4.8 or DeepSeek V4.1 Flash: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 62.5 for DeepSeek V4.1 Flash.

Pick DeepSeek V4.1 Flash for output tokens 29.8x cheaper ($0.84 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).

Shared results
91
Claude Opus 4.8 only
39
DeepSeek V4.1 Flash only
10
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.

At a glance

Coding index
Claude Opus 4.8 65.0 from 6 benchmarks, DeepSeek V4.1 Flash 62.5 from 5 benchmarks.
Widest category
Intelligence, 10.5 points apart on average over 2 shared benchmarks.
Widest single gap
Surface Evolver Bench: Claude Opus 4.8 87.5% against DeepSeek V4.1 Flash 46.3%, 41.3 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against DeepSeek V4.1 Flash $0.84 per million output tokens, 29.8x apart.
Context window
Claude Opus 4.8 takes 1M tokens, DeepSeek V4.1 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
CategoryClaude Opus 4.8BarsDeepSeek V4.1 FlashTies
Coding59
Intelligence20
Agentic work81
Reasoning75
Math501 tie
Knowledge52
Web design18
General266
All shared boards59311 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index59
Coding benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
LiveBench coding77.3%90.2%DeepSeek V4.1 Flash
LMArena WebDev15561618DeepSeek V4.1 Flash
AA Coding Index74.3Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Vals AI)87.8%Not measuredOnly Claude Opus 4.8 measured
SWE-bench Verified (Vals AI)88.6%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 4 (Vals AI)23.2%19.7%Claude Opus 4.8
Vibe Code Bench (Vals AI)82.7%84.7%DeepSeek V4.1 Flash
Code migration (Vals AI)47.3%45.6%Claude Opus 4.8
ProgramBench (Vals AI)1.0%0.5%Claude Opus 4.8
IOI (Vals AI)Not measured40.3%Only DeepSeek V4.1 Flash measured
Terminal-Bench 2.1 (Vals AI)71.9%74.5%DeepSeek V4.1 Flash
SWE-bench Multimodal (Vals AI)Not measured46.5%Only DeepSeek V4.1 Flash measured
Vibe Code Bench 1-100 (Vals AI)Not measured16.4%Only DeepSeek V4.1 Flash measured
SkillsBench (Vals AI)59.2%69.8%DeepSeek V4.1 Flash
CyberBench (Vals AI)Not measured73.7%Only DeepSeek V4.1 Flash measured
SciCode54.4%51.9%Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)58.3%Not measuredOnly Claude Opus 4.8 measured
FrontierCode46.5%43.9%Claude Opus 4.8
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
ALE-BenchNot measured1092.3Only DeepSeek V4.1 Flash measured
LMArena Text: coding14901502DeepSeek V4.1 Flash
LMArena Text: software and IT14881496DeepSeek V4.1 Flash
LMArena WebDev: React15571628DeepSeek V4.1 Flash
LMArena WebDev: HTML15431612DeepSeek V4.1 Flash
LMArena WebDev: from an imageNot measured1606Only DeepSeek V4.1 Flash measured
SciCode12.3%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 12 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
AA Intelligence Index41.824.7Claude Opus 4.8
Epoch Capabilities Index159.0155.9Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index81
Agentic work benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
AA Agentic Index41.9Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building web apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building full-stack apps1249Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building mobile apps1222Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Android apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games1239Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1171Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides1202Not measuredOnly Claude Opus 4.8 measured
Design Arena: spreadsheets1303Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%86.8%DeepSeek V4.1 Flash
LiveBench browser96.0%84.0%Claude Opus 4.8
LiveBench long agentic48.3%40.1%Claude Opus 4.8
SREBench (Vals AI)Not measured0.8%Only DeepSeek V4.1 Flash measured
Finance Agent (Vals AI)53.9%53.5%Claude Opus 4.8
Tax Agent Bench (Vals AI)30.0%26.6%Claude Opus 4.8
Legal Research Bench (Vals AI)43.8%41.4%Claude Opus 4.8
Excel Modeling Benchmark (Vals AI)69.4%57.2%Claude Opus 4.8
BioMysteryBench (Vals AI)Not measured67.8%Only DeepSeek V4.1 Flash measured
Terminal-Bench-Science (Vals AI)4.3%0.0%Claude Opus 4.8
Vals Science IndexNot measured29.6%Only DeepSeek V4.1 Flash measured
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%Not measuredOnly Claude Opus 4.8 measured
APEX-Agents48.9%39.5%Claude Opus 4.8
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index75
Reasoning benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
GPQA Diamond92.4%Not measuredOnly Claude Opus 4.8 measured
LiveBench reasoning89.2%86.7%Claude Opus 4.8
MysteryMechanism (Vals AI)Not measured21.2%Only DeepSeek V4.1 Flash measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)92.0%Not measuredOnly Claude Opus 4.8 measured
Humanity's Last Exam (Artificial Analysis run)48.7%39.2%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%89.8%Claude Opus 4.8
ARC-AGI92.5%94.5%DeepSeek V4.1 Flash
ARC-AGI-272.1%72.9%DeepSeek V4.1 Flash
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%48.0%Claude Opus 4.8
Mystery game puzzles36.0%43.0%DeepSeek V4.1 Flash
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821483DeepSeek V4.1 Flash
LMArena Text: expert15031501Claude Opus 4.8
LMArena Text: hard prompts in English14871488DeepSeek V4.1 Flash
LMArena Vision: diagrams13151297Claude Opus 4.8
LMArena Vision: homework13371307Claude Opus 4.8
Kagi LLM Benchmark88.8%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index50
Math benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
OTIS Mock AIME98.3%98.3%Tie
FrontierMath, tiers 1 to 380.0%67.4%Claude Opus 4.8
FrontierMath, tier 456.1%26.8%Claude Opus 4.8
ProofBench69.0%54.0%Claude Opus 4.8
LMArena Text: math14861478Claude Opus 4.8
LMArena Text: mathematical work14971485Claude 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 index52
Knowledge benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
MMLU Pro89.6%Not measuredOnly Claude Opus 4.8 measured
LegalBench (Vals AI)83.6%83.3%Claude Opus 4.8
CorpFin (Vals AI)66.7%Not measuredOnly Claude Opus 4.8 measured
TaxEval (Vals AI)75.6%Not measuredOnly Claude Opus 4.8 measured
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedCode (Vals AI)53.2%41.2%Claude Opus 4.8
SimpleQA Verified53.0%42.9%Claude Opus 4.8
LMArena Text: science14771469Claude Opus 4.8
LMArena Text: medicine and healthcare14641484DeepSeek V4.1 Flash
LMArena Text: legal and government14771443Claude Opus 4.8
LMArena Text: business and finance14581461DeepSeek V4.1 Flash
FACTS Benchmark Suite53.5%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index18
Web design benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
Design Arena: websites12581308DeepSeek V4.1 Flash
Design Arena: UI components12551312DeepSeek V4.1 Flash
Design Arena: game dev12641330DeepSeek V4.1 Flash
Design Arena: data viz12401291DeepSeek V4.1 Flash
Design Arena: 3D12221355DeepSeek V4.1 Flash
Design Arena: all code categories12551320DeepSeek V4.1 Flash
Design Arena: SVG11951245DeepSeek V4.1 Flash
Design Arena: ASCII art12771265Claude Opus 4.8
LiveBench design78.8%79.2%DeepSeek V4.1 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index266
General benchmarks for Claude Opus 4.8 and DeepSeek V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 FlashLeader
LiveBench data analysis66.0%79.3%DeepSeek V4.1 Flash
Public Benefits Bench (Vals AI)68.1%64.3%Claude Opus 4.8
SAGE (Vals AI)54.8%47.9%Claude Opus 4.8
MedScribe (Vals AI)85.8%85.5%Claude Opus 4.8
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%Not measuredOnly Claude Opus 4.8 measured
Long context reasoning (AA-LCR)77.7%84.0%DeepSeek V4.1 Flash
DTBench94.9%89.9%Claude Opus 4.8
LMCA57.5%47.0%Claude Opus 4.8
Surface Evolver Bench87.5%46.3%Claude Opus 4.8
Furniture assembly42.5%34.2%Claude Opus 4.8
LMArena Text14611464DeepSeek V4.1 Flash
LMArena Text: instruction following14761473Claude Opus 4.8
LMArena Text: creative writing14541437Claude Opus 4.8
LMArena Vision12941278Claude Opus 4.8
LMArena Text: English14681473DeepSeek V4.1 Flash
LMArena Text: non-English14501449Claude Opus 4.8
LMArena Text: Chinese15061501Claude Opus 4.8
LMArena Text: German14721470Claude Opus 4.8
LMArena Text: Japanese14421432Claude Opus 4.8
LMArena Text: Korean14311436DeepSeek V4.1 Flash
LMArena Text: French14811465Claude Opus 4.8
LMArena Text: Spanish14651459Claude Opus 4.8
LMArena Text: Russian14741467Claude Opus 4.8
LMArena Text: Polish14591457Claude Opus 4.8
LMArena Text: multi-turn14761461Claude Opus 4.8
LMArena Text: longer queries14831473Claude Opus 4.8
LMArena Text: writing and language14611450Claude Opus 4.8
LMArena Text: entertainment and media14401445DeepSeek V4.1 Flash
LMArena Vision: English12931288Claude Opus 4.8
LMArena Vision: Chinese13461327Claude Opus 4.8
LMArena Vision: reading text13031282Claude Opus 4.8
LMArena Vision: humor12821260Claude Opus 4.8
LMArena Vision: creative writing13011275Claude Opus 4.8
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 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 V4.1 Flash
BenchmarkClaude Opus 4.8DeepSeek V4.1 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

Claude Opus 4.8$0.018Fits in one request
DeepSeek V4.1 Flash$0.0006Fits in one request

DeepSeek V4.1 Flash costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
DeepSeek V4.1 Flash$0.014Fits in one request

DeepSeek V4.1 Flash costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
DeepSeek V4.1 Flash$0.053Fits in one request

DeepSeek V4.1 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 Claude Opus 4.8 and DeepSeek V4.1 Flash
SpecificationAnthropic Claude Opus 4.8DeepSeek V4.1 Flash
MakerAnthropicDeepSeek
WeightsNo public weights listedOpen weights
ReleasedMay 27, 2026September 10, 2026
Context window1M1.05M
Input $/Mtok$5.00$0.2225
Output $/Mtok$25.00$0.84
Coding index65.062.5
Independent measurements behind it65
Cost per solved task$2.17Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than DeepSeek V4.1 Flash for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 62.5 for DeepSeek V4.1 Flash. Pick DeepSeek V4.1 Flash for output tokens 29.8x cheaper ($0.84 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).

Which is cheaper, Claude Opus 4.8 or DeepSeek V4.1 Flash?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; DeepSeek V4.1 Flash costs $0.2225 and $0.84. Cost per solved task is known for Claude Opus 4.8 only.

Which has the bigger context window, Claude Opus 4.8 or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs DeepSeek V4.1 Flash comparison based on?

91 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 V4.1 Flash's on 5. Where only one model has a result, the page says so instead of naming a winner.

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