GPT-4o-mini vs GPT-6 Luna
GPT-6 Luna leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 38.1 to 6.7, and GPT-6 Luna costs 1.2x less per output token ($0.50 vs $0.60 per million). Updated October 21, 2026; 6 benchmarks have a result for both.
vs boards won of 6 shared
GPT-4o-mini or GPT-6 Luna: which to pick
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
Model AGPT-4o-miniOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-6 LunaOpenAI57.3/1005 independent benchmarksNo cost per solved task
- Shared results
- 6
- GPT-4o-mini only
- 23
- GPT-6 Luna only
- 97
- Like-for-like categories
- 3 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-6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Luna
GPT-6 Luna leads, 38.1 against 6.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6 Luna has a Design Arena: websites result, 1272.
Directional only
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
GPT-6 Luna
GPT-6 Luna takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
GPT-4o-mini $0.0004, GPT-6 Luna $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-4o-mini not benchmarked, GPT-6 Luna 57.3 from 5 benchmarks.
- Widest category
- Reasoning, 46.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- ARC-AGI-2: GPT-4o-mini 0.0% against GPT-6 Luna 59.3%, 59.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against GPT-6 Luna $0.50 per million output tokens, 1.2x apart.
- Context window
- GPT-4o-mini takes 128K tokens, GPT-6 Luna 1.05M.
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-4o-mini | Bars | GPT-6 Luna | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index22 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 84.5% | Only GPT-6 Luna measured |
| LMArena WebDev | Not measured | 1578 | Only GPT-6 Luna measured |
| AA Coding Index | 11.4 | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Vals AI) | 26.4% | Not measured | Only GPT-4o-mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 13.6% | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | Not measured | 81.7% | Only GPT-6 Luna measured |
| Code migration (Vals AI) | Not measured | 42.5% | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only GPT-6 Luna measured |
| IOI (Vals AI) | Not measured | 55.6% | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 73.0% | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 37.5% | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-6 Luna measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | Not measured | Only GPT-4o-mini measured |
| SciCode | Not measured | 54.6% | Only GPT-6 Luna measured |
| FrontierCode | Not measured | 42.4% | Only GPT-6 Luna measured |
| ALE-Bench | Not measured | 1576.9 | Only GPT-6 Luna measured |
| LMArena Text: coding | Not measured | 1437 | Only GPT-6 Luna measured |
| LMArena Text: software and IT | Not measured | 1423 | Only GPT-6 Luna measured |
| LMArena WebDev: React | Not measured | 1573 | Only GPT-6 Luna measured |
| LMArena WebDev: HTML | Not measured | 1595 | Only GPT-6 Luna measured |
| LMArena WebDev: from an image | Not measured | 1571 | Only GPT-6 Luna measured |
| SciCode | 1.5% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 38.1 | GPT-6 Luna |
| Epoch Capabilities Index | 126.5 | 156.8 | GPT-6 Luna |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1191 | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | Not measured | 1158 | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | Not measured | 1128 | Only GPT-6 Luna measured |
| LiveBench research | Not measured | 43.5% | Only GPT-6 Luna measured |
| LiveBench browser | Not measured | 72.0% | Only GPT-6 Luna measured |
| LiveBench long agentic | Not measured | 48.1% | Only GPT-6 Luna measured |
| SREBench (Vals AI) | Not measured | 2.7% | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | Not measured | 49.9% | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | Not measured | 19.9% | Only GPT-6 Luna measured |
| Legal Research Bench (Vals AI) | Not measured | 30.3% | Only GPT-6 Luna measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 4.2% | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 68.5% | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | Not measured | 61.5% | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only GPT-6 Luna measured |
| Vals Science Index | Not measured | 28.4% | Only GPT-6 Luna measured |
| APEX-Agents | Not measured | 44.3% | Only GPT-6 Luna measured |
| SpireClimb | Not measured | 0.0% | Only GPT-6 Luna measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | Not measured | Only GPT-4o-mini measured |
| LiveBench reasoning | Not measured | 81.8% | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | Not measured | 19.4% | Only GPT-6 Luna measured |
| MMMU Pro (Vals AI) | 56.6% | Not measured | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 42.6% | Not measured | Only GPT-4o-mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 38.5% | GPT-6 Luna |
| GPQA Diamond (Epoch AI run) | Not measured | 90.5% | Only GPT-6 Luna measured |
| ARC-AGI | Not measured | 86.7% | Only GPT-6 Luna measured |
| ARC-AGI-2 | 0.0% | 59.3% | GPT-6 Luna |
| Chess puzzles | Not measured | 36.0% | Only GPT-6 Luna measured |
| Mystery game puzzles | Not measured | 7.0% | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | Not measured | 1410 | Only GPT-6 Luna measured |
| LMArena Text: expert | Not measured | 1442 | Only GPT-6 Luna measured |
| LMArena Text: hard prompts in English | Not measured | 1410 | Only GPT-6 Luna measured |
| LMArena Vision: diagrams | Not measured | 1245 | Only GPT-6 Luna measured |
| LMArena Vision: homework | Not measured | 1261 | Only GPT-6 Luna measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| AIME | 11.5% | Not measured | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | Not measured | Only GPT-4o-mini measured |
| AA Math Index | 14.7 | Not measured | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | 14.7% | Not measured | Only GPT-4o-mini measured |
| OTIS Mock AIME | Not measured | 98.9% | Only GPT-6 Luna measured |
| FrontierMath, tiers 1 to 3 | Not measured | 78.9% | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | Not measured | 56.1% | Only GPT-6 Luna measured |
| ProofBench | Not measured | 64.0% | Only GPT-6 Luna measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1409 | Only GPT-6 Luna measured |
| LMArena Text: mathematical work | Not measured | 1427 | Only GPT-6 Luna measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | Not measured | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | 45.5% | Not measured | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | 60.5% | Not measured | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | 54.5% | Not measured | Only GPT-4o-mini measured |
| MedQA (Vals AI) | 72.4% | Not measured | Only GPT-4o-mini measured |
| MedCode (Vals AI) | Not measured | 44.7% | Only GPT-6 Luna measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | Not measured | Only GPT-4o-mini measured |
| SimpleQA Verified | Not measured | 41.4% | Only GPT-6 Luna measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: science | Not measured | 1386 | Only GPT-6 Luna measured |
| LMArena Text: medicine and healthcare | Not measured | 1352 | Only GPT-6 Luna measured |
| LMArena Text: legal and government | Not measured | 1400 | Only GPT-6 Luna measured |
| LMArena Text: business and finance | Not measured | 1388 | Only GPT-6 Luna measured |
| FACTS Benchmark Suite | Not measured | 63.3% | Only GPT-6 Luna measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1272 | Only GPT-6 Luna measured |
| Design Arena: UI components | Not measured | 1297 | Only GPT-6 Luna measured |
| Design Arena: game dev | Not measured | 1260 | Only GPT-6 Luna measured |
| Design Arena: data viz | Not measured | 1215 | Only GPT-6 Luna measured |
| Design Arena: 3D | Not measured | 1217 | Only GPT-6 Luna measured |
| Design Arena: all code categories | Not measured | 1271 | Only GPT-6 Luna measured |
| Design Arena: SVG | Not measured | 1251 | Only GPT-6 Luna measured |
| Design Arena: ASCII art | Not measured | 1153 | Only GPT-6 Luna measured |
| LiveBench design | Not measured | 82.5% | Only GPT-6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | GPT-6 Luna | Leader |
|---|---|---|---|
| Vals Index | Not measured | 52.3% | Only GPT-6 Luna measured |
| LiveBench data analysis | Not measured | 73.4% | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | Not measured | 57.6% | Only GPT-6 Luna measured |
| SAGE (Vals AI) | Not measured | 48.1% | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | Not measured | 83.7% | Only GPT-6 Luna measured |
| IFBench | 31.0% | Not measured | Only GPT-4o-mini measured |
| Long context reasoning (AA-LCR) | Not measured | 83.3% | Only GPT-6 Luna measured |
| DTBench | 54.4% | 90.1% | GPT-6 Luna |
| LMCA | 10.4% | 44.5% | GPT-6 Luna |
| Furniture assembly | Not measured | 44.2% | Only GPT-6 Luna measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini measured |
| LMArena Text | Not measured | 1389 | Only GPT-6 Luna measured |
| LMArena Text: instruction following | Not measured | 1408 | Only GPT-6 Luna measured |
| LMArena Text: creative writing | Not measured | 1363 | Only GPT-6 Luna measured |
| LMArena Vision | Not measured | 1216 | Only GPT-6 Luna measured |
| LMArena Text: English | Not measured | 1393 | Only GPT-6 Luna measured |
| LMArena Text: non-English | Not measured | 1381 | Only GPT-6 Luna measured |
| LMArena Text: Chinese | Not measured | 1427 | Only GPT-6 Luna measured |
| LMArena Text: German | Not measured | 1376 | Only GPT-6 Luna measured |
| LMArena Text: Japanese | Not measured | 1369 | Only GPT-6 Luna measured |
| LMArena Text: Korean | Not measured | 1359 | Only GPT-6 Luna measured |
| LMArena Text: French | Not measured | 1408 | Only GPT-6 Luna measured |
| LMArena Text: Spanish | Not measured | 1391 | Only GPT-6 Luna measured |
| LMArena Text: Russian | Not measured | 1392 | Only GPT-6 Luna measured |
| LMArena Text: Polish | Not measured | 1383 | Only GPT-6 Luna measured |
| LMArena Text: multi-turn | Not measured | 1392 | Only GPT-6 Luna measured |
| LMArena Text: longer queries | Not measured | 1408 | Only GPT-6 Luna measured |
| LMArena Text: writing and language | Not measured | 1384 | Only GPT-6 Luna measured |
| LMArena Text: entertainment and media | Not measured | 1364 | Only GPT-6 Luna measured |
| LMArena Vision: English | Not measured | 1204 | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | Not measured | 1266 | Only GPT-6 Luna measured |
| LMArena Vision: reading text | Not measured | 1225 | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | Not measured | 1205 | Only GPT-6 Luna measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | GPT-6 Luna | 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-4o-mini$0.0004Fits in one request
GPT-6 Luna$0.0003Fits in one request
GPT-6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini$0.0093Fits in one request
GPT-6 Luna$0.0065Fits in one request
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini$0.036Exceeds the context window
GPT-6 Luna$0.025Fits in one request
GPT-6 Luna 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-4o-mini | OpenAI GPT-6 Luna |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | July 18, 2024 | September 22, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.15 | $0.10 |
| Output $/Mtok | $0.60 | $0.50 |
| Coding index | Not benchmarked | 57.3 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini better than GPT-6 Luna for coding?
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4o-mini or GPT-6 Luna?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o-mini or GPT-6 Luna?
GPT-6 Luna, with 1.05M tokens against 128K.
How many benchmarks is the GPT-4o-mini vs GPT-6 Luna comparison based on?
6 benchmarks have a result for both models as of October 21, 2026. GPT-4o-mini's coding index rests on 0 independent benchmarks and GPT-6 Luna's on 5. Where only one model has a result, the page says so instead of naming a winner.