GPT-5.6 Luna vs gpt-oss-20b
GPT-5.6 Luna leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 37.3 to 10.0, and gpt-oss-20b costs 8.0x less per output token ($0.15 vs $1.20 per million). Updated October 22, 2026; 47 benchmarks have a result for both.
GPT-5.6 Luna or gpt-oss-20b: which to pick
Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding.
Pick gpt-oss-20b for output tokens 8.0x cheaper ($0.15 vs $1.20 per million) and work measured by Kagi LLM Benchmark, where it leads.
- Shared results
- 47
- GPT-5.6 Luna only
- 72
- gpt-oss-20b only
- 15
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GPT-5.6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 10.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Luna has a AA Agentic Index result, 42.1.
Directional only
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 68.9%.
Same board, both measured
Math
AIME
No call
Only gpt-oss-20b has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
GPT-5.6 Luna
GPT-5.6 Luna leads, 86.0% against 71.6%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Luna
GPT-5.6 Luna leads, 1255 against 852.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
GPT-5.6 Luna $0.0008, gpt-oss-20b $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Luna has the number, $0.04.
Directional only
At a glance
- Coding index
- GPT-5.6 Luna 58.0 from 6 benchmarks, gpt-oss-20b not benchmarked.
- Widest category
- Web design, 42.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- Design Arena: websites: GPT-5.6 Luna 1255 against gpt-oss-20b 852, 50.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Luna $1.20 against gpt-oss-20b $0.15 per million output tokens, 8.0x apart.
- Context window
- GPT-5.6 Luna takes 1.05M tokens, gpt-oss-20b 131K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.6 Luna | Bars | gpt-oss-20b | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 7 | 1 | ||
| Math | 3 | 0 | ||
| Knowledge | 8 | 0 | ||
| Web design | 2 | 0 | ||
| General | 19 | 0 | ||
| All shared boards | 46 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev | 1518 | Not measured | Only GPT-5.6 Luna measured |
| AA Coding Index | 71.4 | Not measured | Only GPT-5.6 Luna measured |
| LiveCodeBench (Vals AI) | Not measured | 80.4% | Only gpt-oss-20b measured |
| SWE-bench Verified (Vals AI) | 93.0% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 4 (Vals AI) | 11.6% | Not measured | Only GPT-5.6 Luna measured |
| Vibe Code Bench (Vals AI) | 77.1% | Not measured | Only GPT-5.6 Luna measured |
| Code migration (Vals AI) | 44.5% | Not measured | Only GPT-5.6 Luna measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| IOI (Vals AI) | 61.8% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 79.0% | Not measured | Only GPT-5.6 Luna measured |
| Vibe Code Bench 1-100 (Vals AI) | 22.6% | Not measured | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | 60.5% | Not measured | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 77.7% | Only gpt-oss-20b measured |
| SciCode | 53.6% | 38.9% | GPT-5.6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 10.6% | Only gpt-oss-20b measured |
| Terminal-Bench | Not measured | 3.4% | Only gpt-oss-20b measured |
| FrontierCode | 39.8% | Not measured | Only GPT-5.6 Luna measured |
| WeirdML | 60.9% | 40.9% | GPT-5.6 Luna |
| ALE-Bench | 1667.4 | 566.0 | GPT-5.6 Luna |
| LMArena Text: coding | 1466 | 1307 | GPT-5.6 Luna |
| LMArena Text: software and IT | 1463 | 1311 | GPT-5.6 Luna |
| LMArena WebDev: React | 1508 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: HTML | 1520 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: from an image | 1517 | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 6.2% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| AA Intelligence Index | 37.3 | 10.0 | GPT-5.6 Luna |
| Epoch Capabilities Index | 156.5 | 137.7 | GPT-5.6 Luna |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| AA Agentic Index | 42.1 | Not measured | Only GPT-5.6 Luna measured |
| LiveBench research | 51.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench browser | 68.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench long agentic | 30.4% | Not measured | Only GPT-5.6 Luna measured |
| SREBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | 55.0% | Not measured | Only GPT-5.6 Luna measured |
| Tax Agent Bench (Vals AI) | 24.8% | Not measured | Only GPT-5.6 Luna measured |
| Legal Research Bench (Vals AI) | 36.5% | Not measured | Only GPT-5.6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 67.1% | Not measured | Only GPT-5.6 Luna measured |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| Vals Science Index | 25.3% | Not measured | Only GPT-5.6 Luna measured |
| τ²-Bench Telecom | Not measured | 60.2% | Only gpt-oss-20b measured |
| APEX-Agents | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| BALROG | 45.6% | Not measured | Only GPT-5.6 Luna measured |
| Vending-Bench 2 | $4,095 | Not measured | Only GPT-5.6 Luna measured |
| BrowseComp-Plus | Not measured | 50.6% | Only gpt-oss-20b measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | 68.9% | GPT-5.6 Luna |
| LiveBench reasoning | 85.6% | Not measured | Only GPT-5.6 Luna measured |
| MysteryMechanism (Vals AI) | 14.4% | Not measured | Only GPT-5.6 Luna measured |
| MMMU Pro (Vals AI) | 85.0% | Not measured | Only GPT-5.6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 68.8% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 39.5% | 11.0% | GPT-5.6 Luna |
| GPQA Diamond (Epoch AI run) | 91.6% | 60.8% | GPT-5.6 Luna |
| ARC-AGI | 88.0% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | 59.5% | Not measured | Only GPT-5.6 Luna measured |
| SimpleBench | 46.8% | Not measured | Only GPT-5.6 Luna measured |
| Chess puzzles | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| Mystery game puzzles | 21.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: hard prompts | 1451 | 1274 | GPT-5.6 Luna |
| LMArena Text: expert | 1478 | 1258 | GPT-5.6 Luna |
| LMArena Text: hard prompts in English | 1460 | 1292 | GPT-5.6 Luna |
| LMArena Vision: diagrams | 1273 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: homework | 1282 | Not measured | Only GPT-5.6 Luna measured |
| Kagi LLM Benchmark | 49.1% | 53.2% | gpt-oss-20b |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only gpt-oss-20b measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only gpt-oss-20b measured |
| MGSM (Vals AI) | Not measured | 89.0% | Only gpt-oss-20b measured |
| AA Math Index | Not measured | 89.3 | Only gpt-oss-20b measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 89.3% | Only gpt-oss-20b measured |
| OTIS Mock AIME | 98.3% | 65.3% | GPT-5.6 Luna |
| FrontierMath, tiers 1 to 3 | 82.1% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | 61.0% | Not measured | Only GPT-5.6 Luna measured |
| ProofBench | 60.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: math | 1459 | 1317 | GPT-5.6 Luna |
| LMArena Text: mathematical work | 1470 | 1305 | GPT-5.6 Luna |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | 71.6% | GPT-5.6 Luna |
| LegalBench (Vals AI) | 84.0% | 70.8% | GPT-5.6 Luna |
| CaseLaw (Vals AI) | Not measured | 43.8% | Only gpt-oss-20b measured |
| CorpFin (Vals AI) | 64.2% | 53.1% | GPT-5.6 Luna |
| TaxEval (Vals AI) | 76.2% | 63.7% | GPT-5.6 Luna |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Luna measured |
| MedQA (Vals AI) | Not measured | 82.9% | Only gpt-oss-20b measured |
| MedCode (Vals AI) | 42.4% | Not measured | Only GPT-5.6 Luna measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 74.8% | Only gpt-oss-20b measured |
| SimpleQA Verified | 41.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: science | 1433 | 1296 | GPT-5.6 Luna |
| LMArena Text: medicine and healthcare | 1399 | 1310 | GPT-5.6 Luna |
| LMArena Text: legal and government | 1446 | 1280 | GPT-5.6 Luna |
| LMArena Text: business and finance | 1439 | 1284 | GPT-5.6 Luna |
| FACTS Benchmark Suite | 35.0% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| Design Arena: websites | 1255 | 852 | GPT-5.6 Luna |
| Design Arena: UI components | 1248 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: game dev | 1195 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: data viz | 1212 | 933 | GPT-5.6 Luna |
| Design Arena: 3D | 1121 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: all code categories | 1230 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: SVG | 1193 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: ASCII art | 1142 | Not measured | Only GPT-5.6 Luna measured |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| LiveBench data analysis | 78.0% | Not measured | Only GPT-5.6 Luna measured |
| Public Benefits Bench (Vals AI) | 61.2% | Not measured | Only GPT-5.6 Luna measured |
| SAGE (Vals AI) | 44.2% | Not measured | Only GPT-5.6 Luna measured |
| MedScribe (Vals AI) | 84.4% | Not measured | Only GPT-5.6 Luna measured |
| Vals Multimodal Index | 69.1% | Not measured | Only GPT-5.6 Luna measured |
| IFBench | Not measured | 65.1% | Only gpt-oss-20b measured |
| Long context reasoning (AA-LCR) | 83.7% | 34.7% | GPT-5.6 Luna |
| DTBench | 89.1% | 68.0% | GPT-5.6 Luna |
| LMCA | 48.5% | 14.5% | GPT-5.6 Luna |
| Surface Evolver Bench | 61.9% | Not measured | Only GPT-5.6 Luna measured |
| Furniture assembly | 42.5% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text | 1431 | 1288 | GPT-5.6 Luna |
| LMArena Text: instruction following | 1437 | 1236 | GPT-5.6 Luna |
| LMArena Text: creative writing | 1396 | 1201 | GPT-5.6 Luna |
| LMArena Vision | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: English | 1441 | 1303 | GPT-5.6 Luna |
| LMArena Text: non-English | 1417 | 1269 | GPT-5.6 Luna |
| LMArena Text: Chinese | 1470 | 1315 | GPT-5.6 Luna |
| LMArena Text: German | 1455 | 1255 | GPT-5.6 Luna |
| LMArena Text: Japanese | 1415 | 1244 | GPT-5.6 Luna |
| LMArena Text: Korean | 1415 | 1236 | GPT-5.6 Luna |
| LMArena Text: French | 1458 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Spanish | 1446 | 1267 | GPT-5.6 Luna |
| LMArena Text: Russian | 1427 | 1278 | GPT-5.6 Luna |
| LMArena Text: Polish | 1405 | 1252 | GPT-5.6 Luna |
| LMArena Text: multi-turn | 1434 | 1268 | GPT-5.6 Luna |
| LMArena Text: longer queries | 1436 | 1250 | GPT-5.6 Luna |
| LMArena Text: writing and language | 1419 | 1238 | GPT-5.6 Luna |
| LMArena Text: entertainment and media | 1402 | 1216 | GPT-5.6 Luna |
| LMArena Vision: English | 1263 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: Chinese | 1294 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: reading text | 1264 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: humor | 1190 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: creative writing | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Document | 1457 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Luna | gpt-oss-20b | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
gpt-oss-20b costs less
Repository review
50K input + 3K output tokens
gpt-oss-20b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-20b costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.6 Luna | OpenAI gpt-oss-20b |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | August 5, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.20 | $0.03 |
| Output $/Mtok | $1.20 | $0.15 |
| Coding index | 58.0 | Not benchmarked |
| Independent measurements behind it | 6 | 0 |
| Cost per solved task | $0.04 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna better than gpt-oss-20b for coding?
Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding. Pick gpt-oss-20b for output tokens 8.0x cheaper ($0.15 vs $1.20 per million) and work measured by Kagi LLM Benchmark, where it leads.
Which is cheaper, GPT-5.6 Luna or gpt-oss-20b?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; gpt-oss-20b costs $0.03 and $0.15. Cost per solved task is known for GPT-5.6 Luna only.
Which has the bigger context window, GPT-5.6 Luna or gpt-oss-20b?
GPT-5.6 Luna, with 1.05M tokens against 131K.
How many benchmarks is the GPT-5.6 Luna vs gpt-oss-20b comparison based on?
47 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Luna's coding index rests on 6 independent benchmarks and gpt-oss-20b's on 0. Where only one model has a result, the page says so instead of naming a winner.