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DeepSeek V3.2 Exp vs Muse Wonder

Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V3.2 Exp Replace Muse Wonder
DeepSeek V3.2 ExpDeepSeek
Coding
55.0
Overall
16.6
Output $/M
$0.41
0
Muse WonderMeta
Coding
64.5
Overall
No data
Output $/M
$20.00
36
vs boards won of 36 shared

Decision reading

Pick Muse Wonder for coding: it scores 64.5 on the Vibe Coding Index against 55.0 for DeepSeek V3.2 Exp, though on 1 benchmark against 2.

Pick DeepSeek V3.2 Exp when output tokens cost 48.8x less.

Model ADeepSeek V3.2 ExpDeepSeek55.0/1002 independent benchmarksNo cost per solved taskModel BMuse WonderMeta64.5/1001 independent benchmarkNo cost per solved task
Shared results
36
DeepSeek V3.2 Exp only
21
Muse Wonder only
24
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
DeepSeek V3.2 Exp 55.0 from 2 benchmarks, Muse Wonder 64.5 from 1 benchmark.
Widest category
Coding, 33.5 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena WebDev: DeepSeek V3.2 Exp 1272 against Muse Wonder 1652, 54.3 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Muse Wonder $20.00 per million output tokens, 48.8x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Muse Wonder 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
CategoryDeepSeek V3.2 ExpBarsMuse WonderTies
Coding04
Intelligence01
Reasoning04
Math02
Knowledge04
Web design06
General015
All shared boards036
CodingLike-for-likeFour of these boards feed the Vibe Coding Index04
Coding benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev12721652Muse Wonder
Terminal-Bench 4 (Vals AI)Not measured49.5%Only Muse Wonder measured
Vibe Code Bench (Vals AI)Not measured83.1%Only Muse Wonder measured
Code migration (Vals AI)Not measured62.5%Only Muse Wonder measured
IOI (Vals AI)Not measured66.9%Only Muse Wonder measured
SWE-bench Multimodal (Vals AI)Not measured45.6%Only Muse Wonder measured
Vibe Code Bench 1-100 (Vals AI)Not measured26.6%Only Muse Wonder measured
CyberBench (Vals AI)Not measured80.4%Only Muse Wonder measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
SciCodeNot measured60.3%Only Muse Wonder measured
Terminal-Bench Hard (Artificial Analysis run)31.1%Not measuredOnly DeepSeek V3.2 Exp measured
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: coding14381522Muse Wonder
LMArena Text: software and IT14381515Muse Wonder
LMArena WebDev: ReactNot measured1641Only Muse Wonder measured
LMArena WebDev: HTML12811694Muse Wonder
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
AA Intelligence Index16.6Not measuredOnly DeepSeek V3.2 Exp measured
Epoch Capabilities Index144.9161.8Muse Wonder
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Agentic work benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
Design Arena: spreadsheetsNot measured1236Only Muse Wonder measured
Finance Agent (Vals AI)Not measured56.6%Only Muse Wonder measured
Tax Agent Bench (Vals AI)Not measured36.3%Only Muse Wonder measured
Legal Research Bench (Vals AI)Not measured50.5%Only Muse Wonder measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured23.8%Only Muse Wonder measured
Excel Modeling Benchmark (Vals AI)Not measured67.1%Only Muse Wonder measured
BioMysteryBench (Vals AI)Not measured67.0%Only Muse Wonder measured
Terminal-Bench-Science (Vals AI)Not measured22.9%Only Muse Wonder measured
Vals Science IndexNot measured39.1%Only Muse Wonder measured
CUA-bench (Vals AI)Not measured7.2%Only Muse Wonder measured
τ²-Bench Telecom33.9%Not measuredOnly DeepSeek V3.2 Exp measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Vending-Bench 2Not measured$9,432Only Muse Wonder measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
MysteryMechanism (Vals AI)Not measured27.5%Only Muse Wonder measured
GPQA Diamond (Artificial Analysis run)79.7%Not measuredOnly DeepSeek V3.2 Exp measured
Humanity's Last Exam (Artificial Analysis run)14.9%50.1%Muse Wonder
LMArena Text: hard prompts14291506Muse Wonder
LMArena Text: expert14221513Muse Wonder
LMArena Text: hard prompts in English14441506Muse Wonder
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
AA Math Index87.7Not measuredOnly DeepSeek V3.2 Exp measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly DeepSeek V3.2 Exp measured
ProofBenchNot measured84.0%Only Muse Wonder measured
LMArena Text: math14221486Muse Wonder
LMArena Text: mathematical work14331514Muse Wonder
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: science14431506Muse Wonder
LMArena Text: medicine and healthcare14681512Muse Wonder
LMArena Text: legal and government14191505Muse Wonder
LMArena Text: business and finance14121483Muse Wonder
Neither model has a result on the other 12 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
Design Arena: websites11791361Muse Wonder
Design Arena: UI components11661371Muse Wonder
Design Arena: game dev11451380Muse Wonder
Design Arena: data viz11521330Muse Wonder
Design Arena: 3D11481425Muse Wonder
Design Arena: all code categories11711370Muse Wonder
Design Arena: SVG1031Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
Vals IndexNot measured64.9%Only Muse Wonder measured
Public Benefits Bench (Vals AI)Not measured70.2%Only Muse Wonder measured
IFBench54.1%Not measuredOnly DeepSeek V3.2 Exp measured
Long context reasoning (AA-LCR)72.3%80.7%Muse Wonder
DTBench87.7%95.2%Muse Wonder
LMCA29.1%56.8%Muse Wonder
Fiction.LiveBench83.3%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench13.2%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text14251502Muse Wonder
LMArena Text: instruction following14011491Muse Wonder
LMArena Text: creative writing14041491Muse Wonder
LMArena Text: English14411507Muse Wonder
LMArena Text: non-English14041492Muse Wonder
LMArena Text: Chinese14611537Muse Wonder
LMArena Text: German1440Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Japanese1331Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Korean1372Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: French14341523Muse Wonder
LMArena Text: Spanish1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Russian14121522Muse Wonder
LMArena Text: Polish1435Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: multi-turn14221510Muse Wonder
LMArena Text: longer queries14181493Muse Wonder
LMArena Text: writing and language14071496Muse Wonder
LMArena Text: entertainment and media14071482Muse Wonder
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 Exp and Muse Wonder
BenchmarkDeepSeek V3.2 ExpMuse WonderLeader
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

DeepSeek V3.2 Exp$0.0005Fits in one request
Muse Wonder$0.014Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
Muse Wonder$0.260Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
Muse Wonder$1.00Fits in one request

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 DeepSeek V3.2 Exp and Muse Wonder
SpecificationDeepSeek V3.2 ExpMeta Muse Wonder
MakerDeepSeekMeta
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025October 12, 2026
Context window164K1.05M
Input $/Mtok$0.27$4.00
Output $/Mtok$0.41$20.00
Coding index55.064.5
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Muse Wonder for coding?

Pick Muse Wonder for coding: it scores 64.5 on the Vibe Coding Index against 55.0 for DeepSeek V3.2 Exp, though on 1 benchmark against 2. Pick DeepSeek V3.2 Exp when output tokens cost 48.8x less.

Which is cheaper, DeepSeek V3.2 Exp or Muse Wonder?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Muse Wonder costs $4.00 and $20.00. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.2 Exp or Muse Wonder?

Muse Wonder, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Muse Wonder comparison based on?

36 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2 Exp's coding index rests on 2 independent benchmarks and Muse Wonder's on 1. Where only one model has a result, the page says so instead of naming a winner.

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