Model comparison
GPT-5.6 Luna vs Sonar
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 38.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
PerplexitySummary
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 33.7.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $1 / $1 for Sonar.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-5.6 Luna | Sonar | |
|---|---|---|
| Provider | OpenAI | Perplexity |
| Noometry Index | 54.6 | 38.5 |
| Released | 2026-07-09 | 2024-01-01 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $0.20 | $1 |
| Output $ / M tokens | $1.20 | $1 |
| Results tracked | 52 | 7 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), Sonar: 35.7 (#221)
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| CursorBench | 35.9% | — |
| LMArena WebDev | 1519 | — |
| SciCode | 53.6% | — |
| WeirdML | 60.9% | — |
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1466 | — |
| ALE-Bench | 1,667 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Luna: 34.4 (#45), Sonar: —
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| APEX-Agents | 43% | — |
| BALROG | 45.6% | — |
| GDP.pdf | 22.7% | — |
| Vending-Bench 2 | 4,095 | — |
Reasoning GPT-5.6 Luna leads
GPT-5.6 Luna: 47.6 (#43), Sonar: 21.1 (#227)
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| ARC-AGI-2 | 59.5% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 49.1% | — |
| NYT Connections (extended) | 69.4% | — |
| ARC-AGI-1 | 88% | — |
| CritPt | 20.6% | — |
| Chess Puzzles | 40% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1451 | — |
| Mystery Game Puzzles | 21% | — |
| DTBench | 89.1% | — |
| LiveBench Data Analysis | — | 37.9% |
| LMCA | 48.5% | — |
| Surface Evolver Bench | 61.9% | — |
| Epoch Capabilities Index | 156.39 | — |
| LiveBench | — | 46.9% |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Sonar: 33.7 (#200)
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.1% | — |
| FrontierMath Tier 4 | 61% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 60% | — |
| LiveBench Math | — | 41.6% |
| LMArena Math | 1458 | — |
Knowledge Not comparable
GPT-5.6 Luna: 58.5 (#34), Sonar: —
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
| LMArena Expert | 1478 | — |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), Sonar: —
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| LMArena Vision | 1258 | — |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1457 | — |
Multilingual Not comparable
GPT-5.6 Luna: 52.8 (#78), Sonar: —
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1470 | — |
| LMArena French | 1456 | — |
| LMArena German | 1454 | — |
| LMArena Japanese | 1411 | — |
| LMArena Korean | 1415 | — |
| LMArena Russian | 1428 | — |
| LMArena Spanish | 1448 | — |
Instruction Following GPT-5.6 Luna leads
GPT-5.6 Luna: 75.6 (#57), Sonar: 71.4 (#150)
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
GPT-5.6 Luna: 43.9 (#82), Sonar: —
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| LMArena Longer Query | 1436 | — |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), Sonar: 52.6 (#167)
| Benchmark | GPT-5.6 Luna | Sonar |
|---|---|---|
| LMArena Text | 1431 | — |
| LMArena Creative Writing | 1396 | — |
| EQ-Bench Creative Writing | 1829 | — |
| EQ-Bench 4 | 1156 | — |
| LMArena Multi-Turn | 1434 | — |
| LiveBench Language | — | 44.1% |
Frequently asked questions
Is GPT-5.6 Luna better than Sonar?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 38.5 on the Noometry Index.
Which is cheaper, GPT-5.6 Luna or Sonar?
GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; Sonar lists at $1 and $1.
Is GPT-5.6 Luna or Sonar better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 35.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Luna does, with 1.05M tokens against 128K.
How many benchmarks do GPT-5.6 Luna and Sonar share?
0 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Sonar has 7.