Enter opens the highlighted result. Esc closes.

DeepSeek V3.2 Exp vs Muse Spark 1.2

Muse Spark 1.2 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 39.6 to 16.6, and DeepSeek V3.2 Exp costs 10.4x less per output token ($0.41 vs $4.25 per million). Updated October 22, 2026; 42 benchmarks have a result for both.

DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
No data
Output $/M
$0.41
0
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
42
vs boards won of 42 shared

DeepSeek V3.2 Exp or Muse Spark 1.2: which to pick

Only Muse Spark 1.2 has a coding score, 55.7 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 10.4x cheaper ($0.41 vs $4.25 per million).

Shared results
42
DeepSeek V3.2 Exp only
17
Muse Spark 1.2 only
55
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
DeepSeek V3.2 Exp not benchmarked, Muse Spark 1.2 55.7 from 5 benchmarks.
Widest category
Coding, 24.8 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: DeepSeek V3.2 Exp 1281 against Muse Spark 1.2 1543, 43.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Muse Spark 1.2 $4.25 per million output tokens, 10.4x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Muse Spark 1.2 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 Spark 1.2Ties
Coding05
Intelligence02
Reasoning05
Math02
Knowledge04
Web design07
General017
All shared boards042
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LiveBench codingNot measured78.2%Only Muse Spark 1.2 measured
LMArena WebDev12721534Muse Spark 1.2
AA Coding IndexNot measured72.2Only Muse Spark 1.2 measured
SWE-bench Verified (Vals AI)Not measured86.6%Only Muse Spark 1.2 measured
Terminal-Bench 4 (Vals AI)Not measured6.1%Only Muse Spark 1.2 measured
Vibe Code Bench (Vals AI)Not measured79.1%Only Muse Spark 1.2 measured
Code migration (Vals AI)Not measured29.9%Only Muse Spark 1.2 measured
ProgramBench (Vals AI)Not measured0.5%Only Muse Spark 1.2 measured
IOI (Vals AI)Not measured21.8%Only Muse Spark 1.2 measured
Terminal-Bench 2.1 (Vals AI)Not measured69.7%Only Muse Spark 1.2 measured
SkillsBench (Vals AI)Not measured53.0%Only Muse Spark 1.2 measured
CyberBench (Vals AI)Not measured69.5%Only Muse Spark 1.2 measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
SciCodeNot measured57.4%Only Muse Spark 1.2 measured
Terminal-Bench Hard (Artificial Analysis run)31.1%Not measuredOnly DeepSeek V3.2 Exp measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdML39.5%60.3%Muse Spark 1.2
LMArena Text: coding14381505Muse Spark 1.2
LMArena Text: software and IT14381505Muse Spark 1.2
LMArena WebDev: ReactNot measured1526Only Muse Spark 1.2 measured
LMArena WebDev: HTML12811543Muse Spark 1.2
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
AA Intelligence Index16.639.6Muse Spark 1.2
Epoch Capabilities Index144.9155.1Muse Spark 1.2
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
Agentic work benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
AA Agentic IndexNot measured43.2Only Muse Spark 1.2 measured
Design Arena: agents building web appsNot measured1221Only Muse Spark 1.2 measured
Design Arena: agents building full-stack appsNot measured1210Only Muse Spark 1.2 measured
Design Arena: agents building mobile appsNot measured1181Only Muse Spark 1.2 measured
Design Arena: agents building Android appsNot measured1222Only Muse Spark 1.2 measured
Design Arena: agents building gamesNot measured1179Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1085Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1172Only Muse Spark 1.2 measured
LiveBench researchNot measured67.7%Only Muse Spark 1.2 measured
LiveBench browserNot measured36.0%Only Muse Spark 1.2 measured
LiveBench long agenticNot measured21.3%Only Muse Spark 1.2 measured
SREBench (Vals AI)Not measured0.0%Only Muse Spark 1.2 measured
Finance Agent (Vals AI)Not measured60.6%Only Muse Spark 1.2 measured
Tax Agent Bench (Vals AI)Not measured32.8%Only Muse Spark 1.2 measured
Legal Research Bench (Vals AI)Not measured43.8%Only Muse Spark 1.2 measured
Excel Modeling Benchmark (Vals AI)Not measured57.0%Only Muse Spark 1.2 measured
BioMysteryBench (Vals AI)Not measured64.8%Only Muse Spark 1.2 measured
τ²-Bench Telecom33.9%Not measuredOnly DeepSeek V3.2 Exp measured
APEX-AgentsNot measured45.4%Only Muse Spark 1.2 measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Berkeley Function Calling Leaderboard (BFCL)56.7%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
LiveBench reasoningNot measured90.0%Only Muse Spark 1.2 measured
MMMU Pro (Vals AI)Not measured86.1%Only Muse Spark 1.2 measured
GPQA Diamond (Artificial Analysis run)79.7%90.4%Muse Spark 1.2
Humanity's Last Exam (Artificial Analysis run)14.9%45.5%Muse Spark 1.2
SimpleBenchNot measured74.5%Only Muse Spark 1.2 measured
Chess puzzlesNot measured27.0%Only Muse Spark 1.2 measured
LMArena Text: hard prompts14291489Muse Spark 1.2
LMArena Text: expert14221475Muse Spark 1.2
LMArena Text: hard prompts in English14441487Muse Spark 1.2
LMArena Vision: diagramsNot measured1317Only Muse Spark 1.2 measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
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 measured43.0%Only Muse Spark 1.2 measured
LMArena Text: math14221484Muse Spark 1.2
LMArena Text: mathematical work14331480Muse Spark 1.2
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 Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
MMLU ProNot measured88.3%Only Muse Spark 1.2 measured
LegalBench (Vals AI)Not measured85.3%Only Muse Spark 1.2 measured
CorpFin (Vals AI)Not measured70.9%Only Muse Spark 1.2 measured
TaxEval (Vals AI)Not measured80.4%Only Muse Spark 1.2 measured
MortgageTax (Vals AI)Not measured65.4%Only Muse Spark 1.2 measured
MedCode (Vals AI)Not measured49.4%Only Muse Spark 1.2 measured
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
SimpleQA VerifiedNot measured60.3%Only Muse Spark 1.2 measured
LMArena Text: science14431500Muse Spark 1.2
LMArena Text: medicine and healthcare14681496Muse Spark 1.2
LMArena Text: legal and government14191517Muse Spark 1.2
LMArena Text: business and finance14121484Muse Spark 1.2
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
Design Arena: websites11781312Muse Spark 1.2
Design Arena: UI components11641298Muse Spark 1.2
Design Arena: game dev11441301Muse Spark 1.2
Design Arena: data viz11521334Muse Spark 1.2
Design Arena: 3D11481301Muse Spark 1.2
Design Arena: all code categories11701312Muse Spark 1.2
Design Arena: SVG10311284Muse Spark 1.2
Design Arena: ASCII artNot measured1284Only Muse Spark 1.2 measured
LiveBench designNot measured67.1%Only Muse Spark 1.2 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for DeepSeek V3.2 Exp and Muse Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
LiveBench data analysisNot measured76.5%Only Muse Spark 1.2 measured
Public Benefits Bench (Vals AI)Not measured68.5%Only Muse Spark 1.2 measured
SAGE (Vals AI)Not measured47.7%Only Muse Spark 1.2 measured
MedScribe (Vals AI)Not measured90.1%Only Muse Spark 1.2 measured
Vals Multimodal IndexNot measured69.8%Only Muse Spark 1.2 measured
IFBench54.1%Not measuredOnly DeepSeek V3.2 Exp measured
Long context reasoning (AA-LCR)72.3%79.0%Muse Spark 1.2
DTBench87.7%94.7%Muse Spark 1.2
LMCA29.1%48.4%Muse Spark 1.2
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 Text14251482Muse Spark 1.2
LMArena Text: instruction following14011462Muse Spark 1.2
LMArena Text: creative writing14041436Muse Spark 1.2
LMArena VisionNot measured1304Only Muse Spark 1.2 measured
LMArena Text: English14411483Muse Spark 1.2
LMArena Text: non-English14041476Muse Spark 1.2
LMArena Text: Chinese14611509Muse Spark 1.2
LMArena Text: German1440Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Japanese1331Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Korean13721462Muse Spark 1.2
LMArena Text: French14341495Muse Spark 1.2
LMArena Text: Spanish14411484Muse Spark 1.2
LMArena Text: Russian14121483Muse Spark 1.2
LMArena Text: Polish1435Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: multi-turn14221502Muse Spark 1.2
LMArena Text: longer queries14181473Muse Spark 1.2
LMArena Text: writing and language14071453Muse Spark 1.2
LMArena Text: entertainment and media14071443Muse Spark 1.2
LMArena Vision: EnglishNot measured1291Only Muse Spark 1.2 measured
LMArena Vision: reading textNot measured1313Only Muse Spark 1.2 measured
Neither model has a result on the other 14 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 Spark 1.2
BenchmarkDeepSeek V3.2 ExpMuse Spark 1.2Leader
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 Spark 1.2$0.0034Fits 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 Spark 1.2$0.075Fits 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 Spark 1.2$0.292Fits 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 Spark 1.2
SpecificationDeepSeek V3.2 ExpMeta Muse Spark 1.2
MakerDeepSeekMeta
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025August 5, 2026
Context window164K1.05M
Input $/Mtok$0.27$1.25
Output $/Mtok$0.41$4.25
Coding indexNot benchmarked55.7
Independent measurements behind it15
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Muse Spark 1.2 for coding?

Only Muse Spark 1.2 has a coding score, 55.7 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 10.4x cheaper ($0.41 vs $4.25 per million).

Which is cheaper, DeepSeek V3.2 Exp or Muse Spark 1.2?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.2 only.

Which has the bigger context window, DeepSeek V3.2 Exp or Muse Spark 1.2?

Muse Spark 1.2, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Muse Spark 1.2 comparison based on?

42 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Muse Spark 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.

Compare next