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Claude Fable 5.2 vs DeepSeek V4 Pro 0813

Claude Fable 5.2 leads DeepSeek V4 Pro 0813 on coding, 87.8 to 56.1 on the Vibe Coding Index, and DeepSeek V4 Pro 0813 costs 20.2x less per output token ($1.98 vs $40.00 per million). Updated November 14, 2026; 37 benchmarks have a result for both.

Claude Fable 5.2Anthropic
Coding
87.8
Overall
91.7
Output $/M
$40.00
36
DeepSeek V4 Pro 0813DeepSeek
Coding
56.1
Overall
58.0
Output $/M
$1.98
1
vs boards won of 37 shared

Claude Fable 5.2 or DeepSeek V4 Pro 0813: which to pick

Pick Claude Fable 5.2 for coding: it scores 87.8 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813, though on 4 benchmarks against 5.

Pick DeepSeek V4 Pro 0813 for output tokens 20.2x cheaper ($1.98 vs $40.00 per million) and a larger context window (1.05M against 1M tokens).

Shared results
37
Claude Fable 5.2 only
31
DeepSeek V4 Pro 0813 only
50
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.

At a glance

Coding index
Claude Fable 5.2 87.8 from 4 benchmarks, DeepSeek V4 Pro 0813 56.1 from 5 benchmarks.
Widest category
Knowledge, 38.8 points apart on average over 2 shared benchmarks.
Widest single gap
FrontierMath, tier 4: Claude Fable 5.2 100.0% against DeepSeek V4 Pro 0813 26.8%, 73.2 points apart on a 0 to 100 scale.
Output price
Claude Fable 5.2 $40.00 against DeepSeek V4 Pro 0813 $1.98 per million output tokens, 20.2x apart.
Context window
Claude Fable 5.2 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
CategoryClaude Fable 5.2BarsDeepSeek V4 Pro 0813Ties
Coding110
Intelligence20
Agentic work41
Reasoning80
Math40
Knowledge20
General50
All shared boards361
CodingLike-for-likeSix of these boards feed the Vibe Coding Index110
Coding benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
LiveBench coding79.2%Not measuredOnly Claude Fable 5.2 measured
LMArena WebDev18381581Claude Fable 5.2
AA Coding IndexNot measured68.8Only DeepSeek V4 Pro 0813 measured
LiveCodeBench (Vals AI)Not measured87.5%Only DeepSeek V4 Pro 0813 measured
SWE-bench Verified (Vals AI)Not measured96.4%Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 4 (Vals AI)65.2%14.1%Claude Fable 5.2
Vibe Code Bench (Vals AI)93.8%82.3%Claude Fable 5.2
Code migration (Vals AI)Not measured41.5%Only DeepSeek V4 Pro 0813 measured
ProgramBench (Vals AI)19.0%0.0%Claude Fable 5.2
IOI (Vals AI)Not measured51.6%Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)Not measured54.7%Only DeepSeek V4 Pro 0813 measured
SWE-bench Multimodal (Vals AI)62.3%Not measuredOnly Claude Fable 5.2 measured
Vibe Code Bench 1-100 (Vals AI)Not measured17.5%Only DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)Not measured53.8%Only DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)Not measured72.9%Only DeepSeek V4 Pro 0813 measured
SciCode67.7%51.7%Claude Fable 5.2
Terminal-Bench 4.0 (Artificial Analysis run)61.6%14.1%Claude Fable 5.2
FrontierCode 2.049.1%17.1%Claude Fable 5.2
FrontierCodeNot measured28.5%Only DeepSeek V4 Pro 0813 measured
FrontierSWE69.9%Not measuredOnly Claude Fable 5.2 measured
WeirdMLNot measured66.2%Only DeepSeek V4 Pro 0813 measured
MirrorCodeNot measured33.3%Only DeepSeek V4 Pro 0813 measured
ALE-Bench2509.81403.2Claude Fable 5.2
LMArena Text: codingNot measured1467Only DeepSeek V4 Pro 0813 measured
LMArena Text: software and ITNot measured1460Only DeepSeek V4 Pro 0813 measured
LMArena WebDev: React19151586Claude Fable 5.2
LMArena WebDev: HTML17381561Claude Fable 5.2
GameBench 299.153.6Claude Fable 5.2
Terminal-Bench 4.0Not measured6.7%Only DeepSeek V4 Pro 0813 measured
CursorBench 4.060.0%Not measuredOnly Claude Fable 5.2 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
AA Intelligence Index64.623.1Claude Fable 5.2
Epoch Capabilities Index173.4155.9Claude Fable 5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index41
Agentic work benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
AA Agentic IndexNot measured41.3Only DeepSeek V4 Pro 0813 measured
Design Arena: agents building full-stack apps1402Not measuredOnly Claude Fable 5.2 measured
Design Arena: agents building mobile apps1325Not measuredOnly Claude Fable 5.2 measured
Design Arena: spreadsheets1434Not measuredOnly Claude Fable 5.2 measured
LiveBench research94.5%Not measuredOnly Claude Fable 5.2 measured
LiveBench browser86.9%Not measuredOnly Claude Fable 5.2 measured
LiveBench long agentic82.9%Not measuredOnly Claude Fable 5.2 measured
SREBench (Vals AI)Not measured1.9%Only DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)Not measured50.4%Only DeepSeek V4 Pro 0813 measured
Tax Agent Bench (Vals AI)32.1%26.8%Claude Fable 5.2
Legal Research Bench (Vals AI)46.1%40.9%Claude Fable 5.2
Harvey's Legal Agent Benchmark (Vals AI)5.0%10.8%DeepSeek V4 Pro 0813
Excel Modeling Benchmark (Vals AI)Not measured52.8%Only DeepSeek V4 Pro 0813 measured
BioMysteryBench (Vals AI)83.7%Not measuredOnly Claude Fable 5.2 measured
Terminal-Bench-Science (Vals AI)55.7%4.3%Claude Fable 5.2
Vals Science Index63.7%Not measuredOnly Claude Fable 5.2 measured
APEX-Agents80.1%47.3%Claude Fable 5.2
Remote Labor Index41.3%Not measuredOnly Claude Fable 5.2 measured
SpireClimb15.5%Not measuredOnly Claude Fable 5.2 measured
Toolathlon-VerifiedNot measured74.4%Only DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
GPQA DiamondNot measured92.4%Only DeepSeek V4 Pro 0813 measured
LiveBench reasoning88.8%Not measuredOnly Claude Fable 5.2 measured
MysteryMechanism (Vals AI)51.8%Not measuredOnly Claude Fable 5.2 measured
GPQA Diamond (Artificial Analysis run)Not measured92.8%Only DeepSeek V4 Pro 0813 measured
Humanity's Last Exam (Artificial Analysis run)74.3%41.5%Claude Fable 5.2
HLE-Diamond (Artificial Analysis run)80.2%20.5%Claude Fable 5.2
CritPt v2, hard subset (Artificial Analysis run)76.5%28.5%Claude Fable 5.2
GPQA Diamond (Epoch AI run)93.9%91.7%Claude Fable 5.2
ARC-AGI98.5%90.5%Claude Fable 5.2
ARC-AGI-293.8%61.3%Claude Fable 5.2
SimpleBench94.9%Not measuredOnly Claude Fable 5.2 measured
Chess puzzles79.0%46.0%Claude Fable 5.2
Mystery game puzzles90.0%43.0%Claude Fable 5.2
EBR-bench90.5%Not measuredOnly Claude Fable 5.2 measured
LMArena Text: hard promptsNot measured1457Only DeepSeek V4 Pro 0813 measured
LMArena Text: expertNot measured1455Only DeepSeek V4 Pro 0813 measured
LMArena Text: hard prompts in EnglishNot measured1463Only DeepSeek V4 Pro 0813 measured
Humanity's Last Exam (Scale run)72.4%Not measuredOnly Claude Fable 5.2 measured
GoBench2566Not measuredOnly Claude Fable 5.2 measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
OTIS Mock AIME99.7%98.6%Claude Fable 5.2
FrontierMath, tiers 1 to 395.1%64.6%Claude Fable 5.2
FrontierMath, tier 4100.0%26.8%Claude Fable 5.2
ProofBench100.0%50.0%Claude Fable 5.2
LMArena Text: mathNot measured1433Only DeepSeek V4 Pro 0813 measured
LMArena Text: mathematical workNot measured1438Only DeepSeek V4 Pro 0813 measured
MathArena82.8%Not measuredOnly Claude Fable 5.2 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index20
Knowledge benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
MMLU ProNot measured87.0%Only DeepSeek V4 Pro 0813 measured
LegalBench (Vals AI)Not measured82.4%Only DeepSeek V4 Pro 0813 measured
CorpFin (Vals AI)Not measured65.4%Only DeepSeek V4 Pro 0813 measured
TaxEval (Vals AI)Not measured73.1%Only DeepSeek V4 Pro 0813 measured
MedCode (Vals AI)Not measured42.5%Only DeepSeek V4 Pro 0813 measured
AA-Omniscience66.8-6.4Claude Fable 5.2
SimpleQA Verified94.0%52.9%Claude Fable 5.2
LMArena Text: scienceNot measured1457Only DeepSeek V4 Pro 0813 measured
LMArena Text: medicine and healthcareNot measured1446Only DeepSeek V4 Pro 0813 measured
LMArena Text: legal and governmentNot measured1460Only DeepSeek V4 Pro 0813 measured
LMArena Text: business and financeNot measured1442Only DeepSeek V4 Pro 0813 measured
PRBench Finance47.1%Not measuredOnly Claude Fable 5.2 measured
PRBench Legal49.0%Not measuredOnly Claude Fable 5.2 measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
Design Arena: websites1351Not measuredOnly Claude Fable 5.2 measured
Design Arena: UI components1371Not measuredOnly Claude Fable 5.2 measured
Design Arena: game dev1396Not measuredOnly Claude Fable 5.2 measured
Design Arena: 3D1517Not measuredOnly Claude Fable 5.2 measured
Design Arena: all code categories1373Not measuredOnly Claude Fable 5.2 measured
LiveBench design85.1%Not measuredOnly Claude Fable 5.2 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index50
General benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
Vals Index71.3%53.0%Claude Fable 5.2
LiveBench data analysis81.5%Not measuredOnly Claude Fable 5.2 measured
MedScribe (Vals AI)Not measured80.2%Only DeepSeek V4 Pro 0813 measured
Long context reasoning (AA-LCR)83.3%80.3%Claude Fable 5.2
GDPval-AA18311456Claude Fable 5.2
DTBench99.2%93.9%Claude Fable 5.2
LMCA70.6%45.5%Claude Fable 5.2
Furniture assembly90.0%Not measuredOnly Claude Fable 5.2 measured
LMArena TextNot measured1445Only DeepSeek V4 Pro 0813 measured
LMArena Text: instruction followingNot measured1448Only DeepSeek V4 Pro 0813 measured
LMArena Text: creative writingNot measured1437Only DeepSeek V4 Pro 0813 measured
LMArena Text: EnglishNot measured1458Only DeepSeek V4 Pro 0813 measured
LMArena Text: non-EnglishNot measured1429Only DeepSeek V4 Pro 0813 measured
LMArena Text: ChineseNot measured1478Only DeepSeek V4 Pro 0813 measured
LMArena Text: FrenchNot measured1440Only DeepSeek V4 Pro 0813 measured
LMArena Text: SpanishNot measured1436Only DeepSeek V4 Pro 0813 measured
LMArena Text: RussianNot measured1444Only DeepSeek V4 Pro 0813 measured
LMArena Text: multi-turnNot measured1452Only DeepSeek V4 Pro 0813 measured
LMArena Text: longer queriesNot measured1457Only DeepSeek V4 Pro 0813 measured
LMArena Text: writing and languageNot measured1442Only DeepSeek V4 Pro 0813 measured
LMArena Text: entertainment and mediaNot measured1424Only DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 28 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Fable 5.2 and DeepSeek V4 Pro 0813
BenchmarkClaude Fable 5.2DeepSeek V4 Pro 0813Leader
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 Fable 5.2$0.028Fits 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 Fable 5.2$0.520Fits 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 Fable 5.2$2.00Fits 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 Fable 5.2 and DeepSeek V4 Pro 0813
SpecificationAnthropic Claude Fable 5.2DeepSeek V4 Pro 0813
MakerAnthropicDeepSeek
WeightsNo public weights listedOpen weights
ReleasedNovember 9, 2026August 12, 2026
Context window1M1.05M
Input $/Mtok$8.00$0.66
Output $/Mtok$40.00$1.98
Coding index87.856.1
Independent measurements behind it45
Cost per solved taskNot computable$0.10
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Fable 5.2 better than DeepSeek V4 Pro 0813 for coding?

Pick Claude Fable 5.2 for coding: it scores 87.8 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813, though on 4 benchmarks against 5. Pick DeepSeek V4 Pro 0813 for output tokens 20.2x cheaper ($1.98 vs $40.00 per million) and a larger context window (1.05M against 1M tokens).

Which is cheaper, Claude Fable 5.2 or DeepSeek V4 Pro 0813?

Claude Fable 5.2 costs $8.00 per million input tokens and $40.00 per million output tokens; DeepSeek V4 Pro 0813 costs $0.66 and $1.98. Cost per solved task is known for DeepSeek V4 Pro 0813 only.

Which has the bigger context window, Claude Fable 5.2 or DeepSeek V4 Pro 0813?

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

How many benchmarks is the Claude Fable 5.2 vs DeepSeek V4 Pro 0813 comparison based on?

37 benchmarks have a result for both models as of November 14, 2026. Claude Fable 5.2's coding index rests on 4 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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