Model comparison

DeepSeek V4 Pro vs Muse Spark 1.2

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 50.3 on the Noometry Index.

Last verified . 26 shared benchmarks.

DeepSeek V4 Pro DeepSeek

54.3

Rank #31 Confirmed

Muse Spark 1.2 Meta

50.3

Rank #48 Confirmed

Summary

  • They share 26 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 5 categories and Muse Spark 1.2 in 4 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where DeepSeek V4 Pro leads 64.8 to 46.4.
  • The biggest single-benchmark swing is NYT Connections (extended): 91.3% for DeepSeek V4 Pro and 79.2% for Muse Spark 1.2.
  • DeepSeek V4 Pro is cheaper at $0.66 / $1.98 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.2.
  • Muse Spark 1.2 accepts more context: 1.05M tokens versus 1M.
  • DeepSeek V4 Pro has downloadable open weights; the other is API-only.

Side by side

DeepSeek V4 Pro and Muse Spark 1.2 specifications
DeepSeek V4 ProMuse Spark 1.2
ProviderDeepSeekMeta
Noometry Index54.350.3
Released2026-04-242026-08-05
WeightsOpenProprietary
Context window1M1.05M
Max output393K131K
Input $ / M tokens$0.66$1.25
Output $ / M tokens$1.98$4.25
Results tracked4831

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding DeepSeek V4 Pro leads

DeepSeek V4 Pro: 52.4 (#34), Muse Spark 1.2: 49.2 (#51)

Coding benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena WebDev15821533
SciCode51%56.4%
WeirdML66.2%60.3%
LMArena Coding14701495
SWE-bench Verified77.6%—
DeepSWE—54.9%
FrontierCode28.6%—
FrontierSWE—12%
ALE-Bench1,403—

Agentic & Tool Use DeepSeek V4 Pro leads

DeepSeek V4 Pro: 32.8 (#58), Muse Spark 1.2: 29.4 (#87)

Agentic & Tool Use benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
APEX-Agents47.3%36.4%
GDP.pdf—16%
Vending-Bench 23,285—

Reasoning DeepSeek V4 Pro leads

DeepSeek V4 Pro: 56.5 (#24), Muse Spark 1.2: 51.3 (#34)

Reasoning benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
NYT Connections (extended)91.3%79.2%
CritPt18%17.7%
LMArena Hard Prompts14611486
DTBench93.9%94.7%
LMCA45.5%48.4%
Epoch Capabilities Index155.31154.87
ARC-AGI-261.3%—
SimpleBench—74.5%
Kagi LLM Benchmark53.5%—
ARC-AGI-190.5%—
Chess Puzzles47%—
Mystery Game Puzzles43%—
Surface Evolver Bench40%—
ForecastBench56.1—

Math DeepSeek V4 Pro leads

DeepSeek V4 Pro: 64.8 (#30), Muse Spark 1.2: 46.4 (#70)

Math benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
ProofBench50%43%
LMArena Math14551471
FrontierMath (Tiers 1-3)64.6%—
FrontierMath Tier 426.8%—
MathArena Final-Answer Competitions76.6%—
OTIS Mock AIME 2024-202598.6%—

Knowledge DeepSeek V4 Pro leads

DeepSeek V4 Pro: 59.5 (#31), Muse Spark 1.2: 54.1 (#53)

Knowledge benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
SimpleQA Verified52.9%60.3%
LMArena Expert14641480
GPQA Diamond91.7%—
Vectara Hallucination Rate8.6%—

Multimodal Not comparable

DeepSeek V4 Pro: —, Muse Spark 1.2: 43.4 (#25)

Multimodal benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena Vision—1305

Multilingual Muse Spark 1.2 leads

DeepSeek V4 Pro: 54.4 (#45), Muse Spark 1.2: 57.1 (#11)

Multilingual benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena Non-English14391478
LMArena Chinese14861511
LMArena French14721513
LMArena Russian14531487
LMArena Spanish14581498
LMArena German1458—
LMArena Japanese1445—
LMArena Korean1447—

Instruction Following Too close to call

DeepSeek V4 Pro: 76.1 (#47), Muse Spark 1.2: 76.7 (#36)

Instruction Following benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena Instruction Following14481461

Long Context Too close to call

DeepSeek V4 Pro: 45.0 (#51), Muse Spark 1.2: 45.2 (#48)

Long Context benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena Longer Query14581475
CL-bench Life13.5%—

Writing & Preference Muse Spark 1.2 leads

DeepSeek V4 Pro: 65.5 (#46), Muse Spark 1.2: 72.3 (#14)

Writing & Preference benchmarks
BenchmarkDeepSeek V4 ProMuse Spark 1.2
LMArena Text14511482
LMArena Creative Writing14461449
EQ-Bench Creative Writing15531840
LMArena Multi-Turn14671494
EQ-Bench 41166—

Frequently asked questions

Is DeepSeek V4 Pro better than Muse Spark 1.2?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 50.3 on the Noometry Index.

Which is cheaper, DeepSeek V4 Pro or Muse Spark 1.2?

DeepSeek V4 Pro is cheaper. It lists at $0.66 per million input tokens and $1.98 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.

Is DeepSeek V4 Pro or Muse Spark 1.2 better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 49.2 in the Noometry coding category.

Which has the bigger context window?

Muse Spark 1.2 does, with 1.05M tokens against 1M.

How many benchmarks do DeepSeek V4 Pro and Muse Spark 1.2 share?

26 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Muse Spark 1.2 has 31.

Related comparisons

Go deeper