Model comparison

DeepSeek-R1 vs Granite 4.2 3b

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 39.4 on the Noometry Index.

Last verified . 11 shared benchmarks.

DeepSeek-R1 DeepSeek

42.3

Rank #115 Confirmed

Granite 4.2 3b IBM

39.4

Rank #169 Confirmed

Summary

  • They share 11 benchmarks with published results for both. DeepSeek-R1 scores higher in 6 categories and Granite 4.2 3b in 1 category; 7 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where DeepSeek-R1 leads 61.4 to 47.2.
  • Granite 4.2 3b has downloadable open weights; the other is API-only.

Side by side

DeepSeek-R1 and Granite 4.2 3b specifications
DeepSeek-R1Granite 4.2 3b
ProviderDeepSeekIBM
Noometry Index42.339.4
Released2025-01-20—
WeightsProprietaryOpen
Context window164K—
Max output64K—
Input $ / M tokens$0.50—
Output $ / M tokens$2.15—
Results tracked5211

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Category by category

Coding DeepSeek-R1 leads

DeepSeek-R1: 46.3 (#68), Granite 4.2 3b: 40.0 (#151)

Coding benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Coding14271361
Aider Polyglot71.4%—
SciCode35.7%—
WeirdML41.6%—
LiveBench Coding66.7%—
ALE-Bench804.12—
AlgoTune1.7—

Agentic & Tool Use Not comparable

DeepSeek-R1: 30.7 (#75), Granite 4.2 3b: —

Agentic & Tool Use benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
DeepResearch Bench35.1%—
BALROG34.9%—
METR Time Horizons53.8%—

Reasoning Granite 4.2 3b leads

DeepSeek-R1: 18.6 (#278), Granite 4.2 3b: 26.0 (#138)

Reasoning benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Hard Prompts14161306
ARC-AGI-21.3%—
SimpleBench40.8%—
Kagi LLM Benchmark69.4%—
ARC-AGI-121.2%—
CritPt1.1%—
LiveBench Reasoning83.2%—
LiveBench Data Analysis69.8%—
Epoch Capabilities Index141.29—
ForecastBench60—
LiveBench71.6%—

Math Not comparable

DeepSeek-R1: 43.8 (#79), Granite 4.2 3b: —

Math benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
OTIS Mock AIME 2024-202566.4%—
Omni-MATH42.4%—
LiveBench Math80.7%—
LMArena Math1400—
MATH Level 596.6%—

Knowledge DeepSeek-R1 leads

DeepSeek-R1: 44.5 (#87), Granite 4.2 3b: 36.3 (#171)

Knowledge benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Expert13941315
GPQA Diamond76.3%—
MMLU-Pro79.3%—
Confabulations12.7%—
Vectara Hallucination Rate11.3%—
GPQA (HELM)66.6%—

Multilingual DeepSeek-R1 leads

DeepSeek-R1: 52.4 (#85), Granite 4.2 3b: 42.1 (#198)

Multilingual benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Non-English14121268
LMArena Chinese14421269
LMArena Russian14231249
LMArena French1417—
LMArena German1404—
LMArena Japanese1391—
LMArena Korean1360—
LMArena Spanish1411—

Instruction Following DeepSeek-R1 leads

DeepSeek-R1: 72.0 (#143), Granite 4.2 3b: 67.1 (#200)

Instruction Following benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Instruction Following13821273
LiveBench Instruction Following80.5%—
IFEval78.4%—

Long Context DeepSeek-R1 leads

DeepSeek-R1: 45.4 (#36), Granite 4.2 3b: 39.2 (#185)

Long Context benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Longer Query13911291
Fiction.LiveBench75%—

Writing & Preference DeepSeek-R1 leads

DeepSeek-R1: 61.4 (#88), Granite 4.2 3b: 47.2 (#212)

Writing & Preference benchmarks
BenchmarkDeepSeek-R1Granite 4.2 3b
LMArena Text14281293
LMArena Creative Writing14051205
LMArena Multi-Turn14051290
Short-Story Creative Writing83%—
EQ-Bench Creative Writing1500—
WildBench82.8%—
LiveBench Language48.5%—

Frequently asked questions

Is DeepSeek-R1 better than Granite 4.2 3b?

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 39.4 on the Noometry Index.

Is DeepSeek-R1 or Granite 4.2 3b better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 40.0 in the Noometry coding category.

How many benchmarks do DeepSeek-R1 and Granite 4.2 3b share?

11 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Granite 4.2 3b has 11.

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