Model comparison

GPT-5.6 Luna vs Olmo 3.1 32b Think

GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 37.9 on the Noometry Index.

Last verified . 15 shared benchmarks.

GPT-5.6 Luna OpenAI

54.6

Rank #30 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GPT-5.6 Luna scores higher in 8 categories and Olmo 3.1 32b Think in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 36.3.
  • Olmo 3.1 32b Think has downloadable open weights; the other is API-only.

Side by side

GPT-5.6 Luna and Olmo 3.1 32b Think specifications
GPT-5.6 LunaOlmo 3.1 32b Think
ProviderOpenAIAllen Institute for AI (Ai2)
Noometry Index54.637.9
Released2026-07-09—
WeightsProprietaryOpen
Context window1.05M—
Max output128K—
Input $ / M tokens$0.20—
Output $ / M tokens$1.20—
Results tracked5215

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Category by category

Coding GPT-5.6 Luna leads

GPT-5.6 Luna: 54.5 (#28), Olmo 3.1 32b Think: 37.7 (#189)

Coding benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Coding14661291
DeepSWE67.2%—
FrontierCode39.8%—
CursorBench35.9%—
LMArena WebDev1519—
SciCode53.6%—
WeirdML60.9%—
ALE-Bench1,667—

Agentic & Tool Use Not comparable

GPT-5.6 Luna: 34.4 (#45), Olmo 3.1 32b Think: —

Agentic & Tool Use benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
APEX-Agents43%—
BALROG45.6%—
GDP.pdf22.7%—
Vending-Bench 24,095—

Reasoning GPT-5.6 Luna leads

GPT-5.6 Luna: 47.6 (#43), Olmo 3.1 32b Think: 25.2 (#150)

Reasoning benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Hard Prompts14511272
ARC-AGI-259.5%—
SimpleBench46.8%—
Kagi LLM Benchmark49.1%—
NYT Connections (extended)69.4%—
ARC-AGI-188%—
CritPt20.6%—
Chess Puzzles40%—
Mystery Game Puzzles21%—
DTBench89.1%—
LMCA48.5%—
Surface Evolver Bench61.9%—
Epoch Capabilities Index156.39—

Math GPT-5.6 Luna leads

GPT-5.6 Luna: 77.7 (#14), Olmo 3.1 32b Think: 36.3 (#168)

Math benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Math14581305
FrontierMath (Tiers 1-3)82.1%—
FrontierMath Tier 461%—
OTIS Mock AIME 2024-202598.3%—
ProofBench60%—

Knowledge GPT-5.6 Luna leads

GPT-5.6 Luna: 58.5 (#34), Olmo 3.1 32b Think: 35.7 (#181)

Knowledge benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Expert14781295
GPQA Diamond91.6%—
SimpleQA Verified41%—

Multimodal Not comparable

GPT-5.6 Luna: 42.7 (#28), Olmo 3.1 32b Think: —

Multimodal benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Vision1258—
Blueprint-Bench 222.6%—
Furniture Assembly42.5%—
LMArena Document1457—

Multilingual GPT-5.6 Luna leads

GPT-5.6 Luna: 52.8 (#78), Olmo 3.1 32b Think: 38.1 (#231)

Multilingual benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Non-English14171209
LMArena Chinese14701242
LMArena French14561260
LMArena German14541262
LMArena Russian14281193
LMArena Spanish14481289
LMArena Japanese1411—
LMArena Korean1415—

Instruction Following GPT-5.6 Luna leads

GPT-5.6 Luna: 75.6 (#57), Olmo 3.1 32b Think: 65.6 (#218)

Instruction Following benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Instruction Following14371247

Long Context GPT-5.6 Luna leads

GPT-5.6 Luna: 43.9 (#82), Olmo 3.1 32b Think: 38.6 (#195)

Long Context benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Longer Query14361272

Writing & Preference GPT-5.6 Luna leads

GPT-5.6 Luna: 68.0 (#29), Olmo 3.1 32b Think: 46.2 (#220)

Writing & Preference benchmarks
BenchmarkGPT-5.6 LunaOlmo 3.1 32b Think
LMArena Text14311272
LMArena Creative Writing13961226
LMArena Multi-Turn14341252
EQ-Bench Creative Writing1829—
EQ-Bench 41156—

Frequently asked questions

Is GPT-5.6 Luna better than Olmo 3.1 32b Think?

GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 37.9 on the Noometry Index.

Is GPT-5.6 Luna or Olmo 3.1 32b Think better for coding?

GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 37.7 in the Noometry coding category.

How many benchmarks do GPT-5.6 Luna and Olmo 3.1 32b Think share?

15 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Olmo 3.1 32b Think has 15.

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