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Claude Haiku 4.5 vs DeepSeek V3.2 Exp

Claude Haiku 4.5 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 16.9 to 16.6, and DeepSeek V3.2 Exp costs 12.2x less per output token ($0.41 vs $5.00 per million). Updated October 22, 2026; 43 benchmarks have a result for both.

Claude Haiku 4.5Anthropic
Coding
35.6
Overall
41.0
Output $/M
$5.00
12
DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
No data
Output $/M
$0.41
31
vs boards won of 43 shared

Claude Haiku 4.5 or DeepSeek V3.2 Exp: which to pick

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding.

Pick DeepSeek V3.2 Exp for output tokens 12.2x cheaper ($0.41 vs $5.00 per million) and work measured by Epoch Capabilities Index or LMArena Text: hard prompts, where it leads.

Shared results
43
Claude Haiku 4.5 only
52
DeepSeek V3.2 Exp only
16
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 Haiku 4.5 35.6 from 4 benchmarks, DeepSeek V3.2 Exp not benchmarked.
Widest category
Agentic work, 12.0 points apart on average over 1 shared benchmark.
Widest single gap
LMArena Text: Polish: Claude Haiku 4.5 1343 against DeepSeek V3.2 Exp 1435, 15.4 points apart on a 0 to 100 scale.
Output price
Claude Haiku 4.5 $5.00 against DeepSeek V3.2 Exp $0.41 per million output tokens, 12.2x apart.
Context window
Claude Haiku 4.5 takes 200K tokens, DeepSeek V3.2 Exp 164K.

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 Haiku 4.5BarsDeepSeek V3.2 ExpTies
Coding50
Intelligence11
Agentic work10
Reasoning12
Math02
Knowledge04
Web design07
General415
All shared boards1231
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
Aider polyglotNot measured74.2%Only DeepSeek V3.2 Exp measured
SWE-bench Verified66.6%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Multilingual64.7%Not measuredOnly Claude Haiku 4.5 measured
LiveBench coding48.1%Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev13301272Claude Haiku 4.5
AA Coding Index43.9Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Vals AI)41.2%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Verified (Vals AI)66.6%Not measuredOnly Claude Haiku 4.5 measured
Vibe Code Bench (Vals AI)11.4%Not measuredOnly Claude Haiku 4.5 measured
Code migration (Vals AI)7.5%Not measuredOnly Claude Haiku 4.5 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Haiku 4.5 measured
Terminal-Bench 2.1 (Vals AI)43.8%Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured78.9%Only DeepSeek V3.2 Exp measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.1%Only DeepSeek V3.2 Exp measured
Terminal-Bench35.5%Not measuredOnly Claude Haiku 4.5 measured
WeirdML45.4%39.5%Claude Haiku 4.5
LMArena Text: coding14541438Claude Haiku 4.5
LMArena Text: software and IT14391438Claude Haiku 4.5
LMArena WebDev: React1326Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev: HTML13181281Claude Haiku 4.5
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
AA Intelligence Index16.916.6Claude Haiku 4.5
Epoch Capabilities Index142.2144.9DeepSeek V3.2 Exp
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
AA Agentic Index8.0Not measuredOnly Claude Haiku 4.5 measured
LiveBench research42.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench browser40.0%Not measuredOnly Claude Haiku 4.5 measured
LiveBench long agentic11.1%Not measuredOnly Claude Haiku 4.5 measured
Finance Agent (Vals AI)31.0%Not measuredOnly Claude Haiku 4.5 measured
Tax Agent Bench (Vals AI)5.9%Not measuredOnly Claude Haiku 4.5 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly Claude Haiku 4.5 measured
Excel Modeling Benchmark (Vals AI)22.7%Not measuredOnly Claude Haiku 4.5 measured
τ²-Bench TelecomNot measured33.9%Only DeepSeek V3.2 Exp measured
BALROG31.2%Not measuredOnly Claude Haiku 4.5 measured
DeepResearch Bench45.5%Not measuredOnly Claude Haiku 4.5 measured
TheAgentCompanyNot measured42.9%Only DeepSeek V3.2 Exp measured
Vending-Bench 2$459Not measuredOnly Claude Haiku 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)68.7%56.7%Claude Haiku 4.5
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
Reasoning benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
GPQA Diamond72.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench reasoning61.7%Not measuredOnly Claude Haiku 4.5 measured
MMMU Pro (Vals AI)46.1%Not measuredOnly Claude Haiku 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured79.7%Only DeepSeek V3.2 Exp measured
Humanity's Last Exam (Artificial Analysis run)Not measured14.9%Only DeepSeek V3.2 Exp measured
GPQA Diamond (Epoch AI run)71.2%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI47.7%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI-24.0%Not measuredOnly Claude Haiku 4.5 measured
Chess puzzles8.0%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: hard prompts14211429DeepSeek V3.2 Exp
LMArena Text: expert14431422Claude Haiku 4.5
LMArena Text: hard prompts in English14351444DeepSeek V3.2 Exp
Kagi LLM BenchmarkNot measured52.2%Only DeepSeek V3.2 Exp measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
AIME82.7%Not measuredOnly Claude Haiku 4.5 measured
MGSM (Vals AI)92.2%Not measuredOnly Claude Haiku 4.5 measured
AA Math IndexNot measured87.7Only DeepSeek V3.2 Exp measured
AIME 2025 (Artificial Analysis run)Not measured87.7%Only DeepSeek V3.2 Exp measured
OTIS Mock AIME66.7%Not measuredOnly Claude Haiku 4.5 measured
MATH level 596.4%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: math13981422DeepSeek V3.2 Exp
LMArena Text: mathematical work14301433DeepSeek V3.2 Exp
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
MMLU Pro78.7%Not measuredOnly Claude Haiku 4.5 measured
LegalBench (Vals AI)81.2%Not measuredOnly Claude Haiku 4.5 measured
CaseLaw (Vals AI)56.5%Not measuredOnly Claude Haiku 4.5 measured
CorpFin (Vals AI)60.6%Not measuredOnly Claude Haiku 4.5 measured
TaxEval (Vals AI)67.5%Not measuredOnly Claude Haiku 4.5 measured
MortgageTax (Vals AI)62.2%Not measuredOnly Claude Haiku 4.5 measured
MedQA (Vals AI)79.6%Not measuredOnly Claude Haiku 4.5 measured
MedCode (Vals AI)32.7%Not measuredOnly Claude Haiku 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured85.0%Only DeepSeek V3.2 Exp measured
SimpleQA Verified13.2%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: science14061443DeepSeek V3.2 Exp
LMArena Text: medicine and healthcare13941468DeepSeek V3.2 Exp
LMArena Text: legal and government14001419DeepSeek V3.2 Exp
LMArena Text: business and finance14001412DeepSeek V3.2 Exp
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
Design Arena: websites11221178DeepSeek V3.2 Exp
Design Arena: UI components10971164DeepSeek V3.2 Exp
Design Arena: game dev10971144DeepSeek V3.2 Exp
Design Arena: data viz11241152DeepSeek V3.2 Exp
Design Arena: 3D10711148DeepSeek V3.2 Exp
Design Arena: all code categories11141170DeepSeek V3.2 Exp
Design Arena: SVG10251031DeepSeek V3.2 Exp
Design Arena: ASCII art1140Not measuredOnly Claude Haiku 4.5 measured
LiveBench design59.9%Not measuredOnly Claude Haiku 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index415
General benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
LiveBench data analysis59.3%Not measuredOnly Claude Haiku 4.5 measured
Public Benefits Bench (Vals AI)54.3%Not measuredOnly Claude Haiku 4.5 measured
SAGE (Vals AI)31.8%Not measuredOnly Claude Haiku 4.5 measured
MedScribe (Vals AI)85.2%Not measuredOnly Claude Haiku 4.5 measured
Vals Multimodal Index42.9%Not measuredOnly Claude Haiku 4.5 measured
IFBenchNot measured54.1%Only DeepSeek V3.2 Exp measured
Long context reasoning (AA-LCR)Not measured72.3%Only DeepSeek V3.2 Exp measured
DTBench73.6%87.7%DeepSeek V3.2 Exp
LMCA30.9%29.1%Claude Haiku 4.5
Fiction.LiveBenchNot measured83.3%Only DeepSeek V3.2 Exp measured
CL-benchNot measured13.2%Only DeepSeek V3.2 Exp measured
ExploitBench13.7%Not measuredOnly Claude Haiku 4.5 measured
CL-bench LifeNot measured9.5%Only DeepSeek V3.2 Exp measured
LMArena Text13971425DeepSeek V3.2 Exp
LMArena Text: instruction following14141401Claude Haiku 4.5
LMArena Text: creative writing13711404DeepSeek V3.2 Exp
LMArena Text: English14141441DeepSeek V3.2 Exp
LMArena Text: non-English13771404DeepSeek V3.2 Exp
LMArena Text: Chinese14181461DeepSeek V3.2 Exp
LMArena Text: German13741440DeepSeek V3.2 Exp
LMArena Text: Japanese13381331Claude Haiku 4.5
LMArena Text: Korean13461372DeepSeek V3.2 Exp
LMArena Text: French14111434DeepSeek V3.2 Exp
LMArena Text: Spanish14211441DeepSeek V3.2 Exp
LMArena Text: Russian13811412DeepSeek V3.2 Exp
LMArena Text: Polish13431435DeepSeek V3.2 Exp
LMArena Text: multi-turn14091422DeepSeek V3.2 Exp
LMArena Text: longer queries14271418Claude Haiku 4.5
LMArena Text: writing and language13861407DeepSeek V3.2 Exp
LMArena Text: entertainment and media13691407DeepSeek V3.2 Exp
LMArena Document1420Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Haiku 4.5 and DeepSeek V3.2 Exp
BenchmarkClaude Haiku 4.5DeepSeek V3.2 ExpLeader
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 Haiku 4.5$0.0035Fits in one request
DeepSeek V3.2 Exp$0.0005Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

Claude Haiku 4.5$0.065Fits in one request
DeepSeek V3.2 Exp$0.015Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 4.5$0.250Exceeds the context window
DeepSeek V3.2 Exp$0.058Exceeds the context window

DeepSeek V3.2 Exp 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 Haiku 4.5 and DeepSeek V3.2 Exp
SpecificationAnthropic Claude Haiku 4.5DeepSeek V3.2 Exp
MakerAnthropicDeepSeek
WeightsNo public weights listedOpen weights
ReleasedOctober 15, 2025September 29, 2025
Context window200K164K
Input $/Mtok$1.00$0.27
Output $/Mtok$5.00$0.41
Coding index35.6Not benchmarked
Independent measurements behind it41
Cost per solved task$0.56Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Haiku 4.5 better than DeepSeek V3.2 Exp for coding?

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 12.2x cheaper ($0.41 vs $5.00 per million) and work measured by Epoch Capabilities Index or LMArena Text: hard prompts, where it leads.

Which is cheaper, Claude Haiku 4.5 or DeepSeek V3.2 Exp?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; DeepSeek V3.2 Exp costs $0.27 and $0.41. Cost per solved task is known for Claude Haiku 4.5 only.

Which has the bigger context window, Claude Haiku 4.5 or DeepSeek V3.2 Exp?

Claude Haiku 4.5, with 200K tokens against 164K.

How many benchmarks is the Claude Haiku 4.5 vs DeepSeek V3.2 Exp comparison based on?

43 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 4.5's coding index rests on 4 independent benchmarks and DeepSeek V3.2 Exp's on 1. Where only one model has a result, the page says so instead of naming a winner.

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