Model comparison
DeepSeek LLM 67B vs GPT-5.6 Luna
GPT-5.6 Luna is the stronger model overall, scoring 54.7 to 24.8 on the Noometry Index.
Last verified . 14 shared benchmarks.
DeepSeekSummary
- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GPT-5.6 Luna in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.5 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.8% for DeepSeek LLM 67B and 98.3% for GPT-5.6 Luna.
- DeepSeek LLM 67B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek LLM 67B | GPT-5.6 Luna | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 24.8 | 54.7 |
| Released | 2023-11-29 | 2026-07-09 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $0.20 |
| Output $ / M tokens | — | $1.20 |
| Results tracked | 15 | 51 |
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Category by category
Coding GPT-5.6 Luna leads
DeepSeek LLM 67B: 31.3 (#273), GPT-5.6 Luna: 53.9 (#25)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Coding | 1096 | 1466 |
| DeepSWE | — | 67.2% |
| FrontierCode | — | 39.8% |
| CursorBench | — | 35.9% |
| LMArena WebDev | — | 1517 |
| SciCode | — | 53.6% |
| WeirdML | — | 60.9% |
| ALE-Bench | — | 1,667 |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, GPT-5.6 Luna: 35.3 (#37)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| BALROG | — | 45.6% |
| GDP.pdf | — | 22.7% |
| Vending-Bench 2 | — | 4,095 |
Reasoning GPT-5.6 Luna leads
DeepSeek LLM 67B: 15.9 (#300), GPT-5.6 Luna: 47.5 (#38)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| Chess Puzzles | 0% | 40% |
| LMArena Hard Prompts | 1070 | 1452 |
| Epoch Capabilities Index | 110.54 | 156.32 |
| 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% |
| Mystery Game Puzzles | — | 21% |
| DTBench | — | 89.1% |
| LMCA | — | 48.5% |
| Surface Evolver Bench | — | 61.9% |
Math GPT-5.6 Luna leads
DeepSeek LLM 67B: 8.1 (#318), GPT-5.6 Luna: 77.5 (#12)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 98.3% |
| LMArena Math | 1108 | 1455 |
| FrontierMath (Tiers 1-3) | — | 82.1% |
| FrontierMath Tier 4 | — | 61% |
| ProofBench | — | 60% |
| MATH Level 5 | 6.4% | — |
Knowledge GPT-5.6 Luna leads
DeepSeek LLM 67B: 7.1 (#308), GPT-5.6 Luna: 58.6 (#31)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| GPQA Diamond | 24.6% | 91.6% |
| SimpleQA Verified | — | 41% |
| LMArena Expert | — | 1479 |
Multimodal Not comparable
DeepSeek LLM 67B: —, GPT-5.6 Luna: 43.0 (#22)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | — | 1259 |
| Blueprint-Bench 2 | — | 22.6% |
| Furniture Assembly | — | 42.5% |
| LMArena Document | — | 1457 |
Multilingual GPT-5.6 Luna leads
DeepSeek LLM 67B: 29.5 (#262), GPT-5.6 Luna: 53.0 (#73)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1073 | 1418 |
| LMArena Chinese | 1132 | 1469 |
| LMArena French | — | 1457 |
| LMArena German | — | 1459 |
| LMArena Japanese | — | 1416 |
| LMArena Korean | — | 1414 |
| LMArena Russian | — | 1428 |
| LMArena Spanish | — | 1445 |
Instruction Following GPT-5.6 Luna leads
DeepSeek LLM 67B: 55.7 (#272), GPT-5.6 Luna: 76.0 (#48)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1079 | 1440 |
Long Context GPT-5.6 Luna leads
DeepSeek LLM 67B: 33.1 (#260), GPT-5.6 Luna: 43.9 (#78)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1092 | 1437 |
Writing & Preference GPT-5.6 Luna leads
DeepSeek LLM 67B: 31.8 (#277), GPT-5.6 Luna: 68.3 (#27)
| Benchmark | DeepSeek LLM 67B | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1105 | 1432 |
| LMArena Creative Writing | 1067 | 1397 |
| LMArena Multi-Turn | 1082 | 1433 |
| EQ-Bench Creative Writing | — | 1829 |
| EQ-Bench 4 | — | 1156 |
Frequently asked questions
Is DeepSeek LLM 67B better than GPT-5.6 Luna?
GPT-5.6 Luna is the stronger model overall, scoring 54.7 to 24.8 on the Noometry Index.
Is DeepSeek LLM 67B or GPT-5.6 Luna better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 53.9 versus 31.3 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and GPT-5.6 Luna share?
14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GPT-5.6 Luna has 51.