R1 0528 vs GPT-6 Luna
Updated October 21, 2026. 43 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
R1 0528 and GPT-6 Luna are level for coding, 71.4 against 71.4 on the Vibe Coding Index, so price and context decide.
Pick GPT-6 Luna when output tokens cost 4.3x less, or when the context window is larger, 1.05M against 164K tokens. Pick R1 0528 when what matters is LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
- Shared results
- 43
- R1 0528 only
- 16
- GPT-6 Luna only
- 59
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
No call
Level: 71.4 against 71.4, inside 2 points.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6 Luna
GPT-6 Luna leads, 38.1 against 13.1.
Same board, both measured
Web design
Design Arena: websites
GPT-6 Luna
GPT-6 Luna leads, 1272 against 1149.
Same board, both measured
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 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
R1 0528 $0.0016, GPT-6 Luna $0.0003 per turn.
List prices
At a glance
- Coding index
- R1 0528 71.4 from 1 benchmark, GPT-6 Luna 71.4 from 2 benchmarks.
- Widest category
- Intelligence, 25.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ARC-AGI: R1 0528 21.2% against GPT-6 Luna 86.7%, 65.5 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.15 against GPT-6 Luna $0.50 per million output tokens, 4.3x apart.
- Context window
- R1 0528 takes 164K 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 | R1 0528 | Bars | GPT-6 Luna | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 2 | 5 | ||
| Math | 0 | 3 | ||
| Knowledge | 4 | 0 | ||
| Web design | 0 | 7 | ||
| General | 15 | 3 | ||
| All shared boards | 22 | 21 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index12
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | Not measured | Only R1 0528 measured |
| LiveBench coding | Not measured | 84.5% | Only GPT-6 Luna measured |
| LMArena WebDev | Not measured | 1578 | Only GPT-6 Luna 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) | 77.0% | Not measured | Only R1 0528 measured |
| SciCode | Not measured | 54.6% | Only GPT-6 Luna measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only R1 0528 measured |
| FrontierCode | Not measured | 42.4% | Only GPT-6 Luna measured |
| WeirdML | 41.6% | Not measured | Only R1 0528 measured |
| ALE-Bench | 804.1 | 1576.9 | GPT-6 Luna |
| LMArena Text: coding | 1427 | 1437 | GPT-6 Luna |
| LMArena Text: software and IT | 1435 | 1423 | R1 0528 |
| 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 |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 38.1 | GPT-6 Luna |
| Epoch Capabilities Index | Not measured | 156.8 | Only GPT-6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1189 | 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 | 1133 | 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 |
| τ²-Bench Telecom | 36.5% | Not measured | Only R1 0528 measured |
| APEX-Agents | Not measured | 44.3% | Only GPT-6 Luna measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| SpireClimb | Not measured | 0.0% | Only GPT-6 Luna measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 81.8% | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | Not measured | 19.4% | Only GPT-6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 81.3% | Not measured | Only R1 0528 measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 38.5% | GPT-6 Luna |
| GPQA Diamond (Epoch AI run) | 76.3% | 90.5% | GPT-6 Luna |
| ARC-AGI | 21.2% | 86.7% | GPT-6 Luna |
| ARC-AGI-2 | 1.1% | 59.3% | GPT-6 Luna |
| SimpleBench | 40.8% | Not measured | Only R1 0528 measured |
| 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 | 1415 | 1410 | R1 0528 |
| LMArena Text: expert | 1394 | 1442 | GPT-6 Luna |
| LMArena Text: hard prompts in English | 1422 | 1410 | R1 0528 |
| LMArena Vision: diagrams | Not measured | 1245 | Only GPT-6 Luna measured |
| LMArena Vision: homework | Not measured | 1261 | Only GPT-6 Luna measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Math Index | 76.0 | Not measured | Only R1 0528 measured |
| AIME 2025 (Artificial Analysis run) | 76.0% | Not measured | Only R1 0528 measured |
| OTIS Mock AIME | 66.4% | 98.9% | GPT-6 Luna |
| 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 |
| MATH level 5 | 96.6% | Not measured | Only R1 0528 measured |
| LMArena Text: math | 1400 | 1409 | GPT-6 Luna |
| LMArena Text: mathematical work | 1415 | 1427 | GPT-6 Luna |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 44.7% | Only GPT-6 Luna measured |
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| SimpleQA Verified | Not measured | 41.4% | Only GPT-6 Luna measured |
| LMArena Text: science | 1430 | 1386 | R1 0528 |
| LMArena Text: medicine and healthcare | 1445 | 1352 | R1 0528 |
| LMArena Text: legal and government | 1419 | 1400 | R1 0528 |
| LMArena Text: business and finance | 1402 | 1388 | R1 0528 |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | R1 0528 | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | 1272 | GPT-6 Luna |
| Design Arena: UI components | 1102 | 1297 | GPT-6 Luna |
| Design Arena: game dev | 1098 | 1259 | GPT-6 Luna |
| Design Arena: data viz | 1182 | 1215 | GPT-6 Luna |
| Design Arena: 3D | 1111 | 1217 | GPT-6 Luna |
| Design Arena: all code categories | 1139 | 1271 | GPT-6 Luna |
| Design Arena: SVG | 1038 | 1253 | GPT-6 Luna |
| Design Arena: ASCII art | Not measured | 1156 | 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 index153
| Benchmark | R1 0528 | 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 | 39.6% | Not measured | Only R1 0528 measured |
| Long context reasoning (AA-LCR) | 55.7% | 83.3% | GPT-6 Luna |
| DTBench | Not measured | 90.1% | Only GPT-6 Luna measured |
| LMCA | Not measured | 44.5% | Only GPT-6 Luna measured |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | Not measured | Only R1 0528 measured |
| Furniture assembly | Not measured | 44.2% | Only GPT-6 Luna measured |
| LMArena Text | 1428 | 1389 | R1 0528 |
| LMArena Text: instruction following | 1382 | 1408 | GPT-6 Luna |
| LMArena Text: creative writing | 1405 | 1363 | R1 0528 |
| LMArena Vision | Not measured | 1216 | Only GPT-6 Luna measured |
| LMArena Text: English | 1437 | 1393 | R1 0528 |
| LMArena Text: non-English | 1412 | 1381 | R1 0528 |
| LMArena Text: Chinese | 1442 | 1427 | R1 0528 |
| LMArena Text: German | 1404 | 1376 | R1 0528 |
| LMArena Text: Japanese | 1391 | 1369 | R1 0528 |
| LMArena Text: Korean | 1360 | 1359 | R1 0528 |
| LMArena Text: French | 1417 | 1408 | R1 0528 |
| LMArena Text: Spanish | 1411 | 1391 | R1 0528 |
| LMArena Text: Russian | 1423 | 1392 | R1 0528 |
| LMArena Text: Polish | 1428 | 1383 | R1 0528 |
| LMArena Text: multi-turn | 1405 | 1392 | R1 0528 |
| LMArena Text: longer queries | 1391 | 1408 | GPT-6 Luna |
| LMArena Text: writing and language | 1402 | 1384 | R1 0528 |
| LMArena Text: entertainment and media | 1400 | 1364 | R1 0528 |
| 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 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | R1 0528 | 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-6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
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 | DeepSeek R1 0528 | OpenAI GPT-6 Luna |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | May 28, 2025 | September 22, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.50 | $0.10 |
| Output $/Mtok | $2.15 | $0.50 |
| Coding index | 71.4 | 71.4 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is R1 0528 better than GPT-6 Luna for coding?
R1 0528 and GPT-6 Luna are level for coding, 71.4 against 71.4 on the Vibe Coding Index, so price and context decide. Pick GPT-6 Luna when output tokens cost 4.3x less, or when the context window is larger, 1.05M against 164K tokens. Pick R1 0528 when what matters is LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
Which is cheaper, R1 0528 or GPT-6 Luna?
R1 0528 costs $0.50 per million input tokens and $2.15 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, R1 0528 or GPT-6 Luna?
GPT-6 Luna, with 1.05M tokens against 164K.
How many benchmarks is the R1 0528 vs GPT-6 Luna comparison based on?
43 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 1 independent benchmark and GPT-6 Luna's on 2. Where only one model has a result, the page says so instead of naming a winner.