GPT-6 Luna vs Beam 1.0 501B A23B
Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-6 Luna for coding: it scores 71.4 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B.
Pick Beam 1.0 501B A23B when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 28
- GPT-6 Luna only
- 74
- Beam 1.0 501B A23B only
- 0
- Like-for-like categories
- 6 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
GPT-6 Luna
GPT-6 Luna scores 71.4 against 33.8.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6 Luna has a AA Intelligence Index result, 38.1.
Directional only
Web design
Design Arena: websites
GPT-6 Luna
GPT-6 Luna leads, 1272 against 1253.
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 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
GPT-6 Luna $0.0003, Beam 1.0 501B A23B $0.0008 per turn.
List prices
At a glance
- Coding index
- GPT-6 Luna 71.4 from 2 benchmarks, Beam 1.0 501B A23B 33.8 from 1 benchmark.
- Widest category
- Coding, 16.1 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: GPT-6 Luna 1595 against Beam 1.0 501B A23B 1436, 26.5 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Luna $0.50 against Beam 1.0 501B A23B $1.00 per million output tokens, 2.0x apart.
- Context window
- GPT-6 Luna takes 1.05M tokens, Beam 1.0 501B A23B 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-6 Luna | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 3 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 2 | 0 | ||
| General | 1 | 11 | ||
| All shared boards | 6 | 22 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index32
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev | 1578 | 1437 | GPT-6 Luna |
| Terminal-Bench 4 (Vals AI) | 13.6% | Not measured | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | 81.7% | Not measured | Only GPT-6 Luna measured |
| Code migration (Vals AI) | 42.5% | Not measured | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-6 Luna measured |
| IOI (Vals AI) | 55.6% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 73.0% | Not measured | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | 37.5% | Not measured | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | 76.3% | Not measured | Only GPT-6 Luna measured |
| SciCode | 54.6% | Not measured | Only GPT-6 Luna measured |
| FrontierCode | 42.4% | Not measured | Only GPT-6 Luna measured |
| ALE-Bench | 1576.9 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: coding | 1437 | 1473 | Beam 1.0 501B A23B |
| LMArena Text: software and IT | 1423 | 1461 | Beam 1.0 501B A23B |
| LMArena WebDev: React | 1573 | 1443 | GPT-6 Luna |
| LMArena WebDev: HTML | 1595 | 1436 | GPT-6 Luna |
| LMArena WebDev: from an image | 1571 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.1 | Not measured | Only GPT-6 Luna measured |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1189 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | 1158 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | 1133 | Not measured | Only GPT-6 Luna measured |
| LiveBench research | 43.5% | Not measured | Only GPT-6 Luna measured |
| LiveBench browser | 72.0% | Not measured | Only GPT-6 Luna measured |
| LiveBench long agentic | 48.1% | Not measured | Only GPT-6 Luna measured |
| SREBench (Vals AI) | 2.7% | Not measured | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | 49.9% | Not measured | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | 19.9% | Not measured | Only GPT-6 Luna measured |
| Legal Research Bench (Vals AI) | 30.3% | Not measured | Only GPT-6 Luna measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 68.5% | Not measured | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only GPT-6 Luna measured |
| Vals Science Index | 28.4% | Not measured | Only GPT-6 Luna measured |
| APEX-Agents | 44.3% | Not measured | Only GPT-6 Luna measured |
| SpireClimb | 0.0% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench reasoning | 81.8% | Not measured | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | 19.4% | Not measured | Only GPT-6 Luna measured |
| Humanity's Last Exam (Artificial Analysis run) | 38.5% | Not measured | Only GPT-6 Luna measured |
| GPQA Diamond (Epoch AI run) | 90.5% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI | 86.7% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI-2 | 59.3% | Not measured | Only GPT-6 Luna measured |
| Chess puzzles | 36.0% | Not measured | Only GPT-6 Luna measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | 1410 | 1442 | Beam 1.0 501B A23B |
| LMArena Text: expert | 1442 | 1447 | Beam 1.0 501B A23B |
| LMArena Text: hard prompts in English | 1410 | 1451 | Beam 1.0 501B A23B |
| LMArena Vision: diagrams | 1245 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: homework | 1261 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tiers 1 to 3 | 78.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | 56.1% | Not measured | Only GPT-6 Luna measured |
| ProofBench | 64.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: math | 1409 | 1459 | Beam 1.0 501B A23B |
| LMArena Text: mathematical work | 1427 | 1475 | Beam 1.0 501B A23B |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 44.7% | Not measured | Only GPT-6 Luna measured |
| SimpleQA Verified | 41.4% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: science | 1386 | 1430 | Beam 1.0 501B A23B |
| LMArena Text: medicine and healthcare | 1352 | 1376 | Beam 1.0 501B A23B |
| LMArena Text: legal and government | 1400 | 1433 | Beam 1.0 501B A23B |
| LMArena Text: business and finance | 1388 | 1430 | Beam 1.0 501B A23B |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1272 | 1253 | GPT-6 Luna |
| Design Arena: UI components | 1297 | Not measured | Only GPT-6 Luna measured |
| Design Arena: game dev | 1259 | 1222 | GPT-6 Luna |
| Design Arena: data viz | 1215 | Not measured | Only GPT-6 Luna measured |
| Design Arena: 3D | 1217 | Not measured | Only GPT-6 Luna measured |
| Design Arena: all code categories | 1271 | Not measured | Only GPT-6 Luna measured |
| Design Arena: SVG | 1253 | Not measured | Only GPT-6 Luna measured |
| Design Arena: ASCII art | 1156 | Not measured | Only GPT-6 Luna measured |
| LiveBench design | 82.5% | Not measured | Only GPT-6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Vals Index | 52.3% | Not measured | Only GPT-6 Luna measured |
| LiveBench data analysis | 73.4% | Not measured | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | 57.6% | Not measured | Only GPT-6 Luna measured |
| SAGE (Vals AI) | 48.1% | Not measured | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | 83.7% | Not measured | Only GPT-6 Luna measured |
| Long context reasoning (AA-LCR) | 83.3% | Not measured | Only GPT-6 Luna measured |
| DTBench | 90.1% | Not measured | Only GPT-6 Luna measured |
| LMCA | 44.5% | Not measured | Only GPT-6 Luna measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-6 Luna measured |
| LMArena Text | 1389 | 1425 | Beam 1.0 501B A23B |
| LMArena Text: instruction following | 1408 | 1430 | Beam 1.0 501B A23B |
| LMArena Text: creative writing | 1363 | 1390 | Beam 1.0 501B A23B |
| LMArena Vision | 1216 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: English | 1393 | 1436 | Beam 1.0 501B A23B |
| LMArena Text: non-English | 1381 | 1413 | Beam 1.0 501B A23B |
| LMArena Text: Chinese | 1427 | 1424 | GPT-6 Luna |
| LMArena Text: German | 1376 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Japanese | 1369 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Korean | 1359 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: French | 1408 | 1461 | Beam 1.0 501B A23B |
| LMArena Text: Spanish | 1391 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Russian | 1392 | 1412 | Beam 1.0 501B A23B |
| LMArena Text: Polish | 1383 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: multi-turn | 1392 | 1414 | Beam 1.0 501B A23B |
| LMArena Text: longer queries | 1408 | 1429 | Beam 1.0 501B A23B |
| LMArena Text: writing and language | 1384 | 1400 | Beam 1.0 501B A23B |
| LMArena Text: entertainment and media | 1364 | 1399 | Beam 1.0 501B A23B |
| LMArena Vision: English | 1204 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | 1266 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: reading text | 1225 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | 1205 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Luna | Beam 1.0 501B A23B | 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 | OpenAI GPT-6 Luna | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | October 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.10 | $0.30 |
| Output $/Mtok | $0.50 | $1.00 |
| Coding index | 71.4 | 33.8 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Luna better than Beam 1.0 501B A23B for coding?
Pick GPT-6 Luna for coding: it scores 71.4 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B. Pick Beam 1.0 501B A23B when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-6 Luna or Beam 1.0 501B A23B?
GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; Beam 1.0 501B A23B costs $0.30 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Luna or Beam 1.0 501B A23B?
GPT-6 Luna, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6 Luna vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. GPT-6 Luna's coding index rests on 2 independent benchmarks and Beam 1.0 501B A23B's on 1. Where only one model has a result, the page says so instead of naming a winner.