GPT-6.1 Sol vs Beam 1.0 501B A23B
Beam 1.0 501B A23B costs 9.1x less per output token than GPT-6.1 Sol ($1.10 vs $10.00 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
GPT-6.1 Sol or Beam 1.0 501B A23B: which to pick
Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Beam 1.0 501B A23B has none, so the two cannot be ranked on coding.
Pick Beam 1.0 501B A23B for output tokens 9.1x cheaper ($1.10 vs $10.00 per million) and work measured by LMArena Text: French, where it leads.
- Shared results
- 28
- GPT-6.1 Sol only
- 70
- Beam 1.0 501B A23B only
- 0
- Like-for-like categories
- 6 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-6.1 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Sol has a AA Intelligence Index result, 51.8.
Directional only
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1250.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
GPT-6.1 Sol $0.0070, Beam 1.0 501B A23B $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-6.1 Sol 82.4 from 5 benchmarks, Beam 1.0 501B A23B not benchmarked.
- Widest category
- Coding, 20.4 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: GPT-6.1 Sol 1753 against Beam 1.0 501B A23B 1437, 45.2 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Sol $10.00 against Beam 1.0 501B A23B $1.10 per million output tokens, 9.1x apart.
- Context window
- GPT-6.1 Sol 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-6.1 Sol | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 2 | 0 | ||
| General | 11 | 1 | ||
| All shared boards | 27 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev | 1753 | 1437 | GPT-6.1 Sol |
| Terminal-Bench 4 (Vals AI) | 55.0% | Not measured | Only GPT-6.1 Sol measured |
| Vibe Code Bench (Vals AI) | 88.9% | Not measured | Only GPT-6.1 Sol measured |
| Code migration (Vals AI) | 65.1% | Not measured | Only GPT-6.1 Sol measured |
| ProgramBench (Vals AI) | 3.0% | Not measured | Only GPT-6.1 Sol measured |
| IOI (Vals AI) | 96.9% | Not measured | Only GPT-6.1 Sol measured |
| SWE-bench Multimodal (Vals AI) | 43.5% | Not measured | Only GPT-6.1 Sol measured |
| CyberBench (Vals AI) | 39.3% | Not measured | Only GPT-6.1 Sol measured |
| SciCode | 55.8% | Not measured | Only GPT-6.1 Sol measured |
| FrontierCode | 50.2% | Not measured | Only GPT-6.1 Sol measured |
| ALE-Bench | 2743.8 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: coding | 1478 | 1473 | GPT-6.1 Sol |
| LMArena Text: software and IT | 1476 | 1461 | GPT-6.1 Sol |
| LMArena WebDev: React | 1754 | 1443 | GPT-6.1 Sol |
| LMArena WebDev: HTML | 1800 | 1436 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1702 | Not measured | Only GPT-6.1 Sol measured |
| SciCode | 9.2% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.8 | Not measured | Only GPT-6.1 Sol measured |
| Epoch Capabilities Index | 168.4 | Not measured | Only GPT-6.1 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1306 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: agents building mobile apps | 1213 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | 1259 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench research | 83.5% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench browser | 88.0% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench long agentic | 73.0% | Not measured | Only GPT-6.1 Sol measured |
| SREBench (Vals AI) | 50.8% | Not measured | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | 52.0% | Not measured | Only GPT-6.1 Sol measured |
| Tax Agent Bench (Vals AI) | 21.8% | Not measured | Only GPT-6.1 Sol measured |
| Legal Research Bench (Vals AI) | 38.5% | Not measured | Only GPT-6.1 Sol measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 6.3% | Not measured | Only GPT-6.1 Sol measured |
| Excel Modeling Benchmark (Vals AI) | 70.8% | Not measured | Only GPT-6.1 Sol measured |
| BioMysteryBench (Vals AI) | 79.6% | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | 52.9% | Not measured | Only GPT-6.1 Sol measured |
| Vals Science Index | 59.6% | Not measured | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | 28.3% | Not measured | Only GPT-6.1 Sol measured |
| APEX-Agents | 60.0% | Not measured | Only GPT-6.1 Sol measured |
| SpireClimb | 24.7% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.6% | Not measured | Only GPT-6.1 Sol measured |
| MysteryMechanism (Vals AI) | 46.4% | Not measured | Only GPT-6.1 Sol measured |
| Humanity's Last Exam (Artificial Analysis run) | 52.9% | Not measured | Only GPT-6.1 Sol measured |
| GPQA Diamond (Epoch AI run) | 95.4% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | 94.2% | Not measured | Only GPT-6.1 Sol measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-6.1 Sol measured |
| Mystery game puzzles | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| EBR-bench | 54.3% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1463 | 1442 | GPT-6.1 Sol |
| LMArena Text: expert | 1489 | 1447 | GPT-6.1 Sol |
| LMArena Text: hard prompts in English | 1465 | 1451 | GPT-6.1 Sol |
| LMArena Vision: diagrams | 1306 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: homework | 1356 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tier 4 | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| ProofBench | 99.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: math | 1489 | 1459 | GPT-6.1 Sol |
| LMArena Text: mathematical work | 1513 | 1475 | GPT-6.1 Sol |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.8% | Not measured | Only GPT-6.1 Sol measured |
| SimpleQA Verified | 73.9% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1444 | 1430 | GPT-6.1 Sol |
| LMArena Text: medicine and healthcare | 1433 | 1376 | GPT-6.1 Sol |
| LMArena Text: legal and government | 1471 | 1433 | GPT-6.1 Sol |
| LMArena Text: business and finance | 1445 | 1430 | GPT-6.1 Sol |
| FACTS Benchmark Suite | 75.3% | Not measured | Only GPT-6.1 Sol measured |
| 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-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1321 | 1250 | GPT-6.1 Sol |
| Design Arena: UI components | 1317 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: game dev | 1389 | 1224 | GPT-6.1 Sol |
| Design Arena: data viz | 1281 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: 3D | 1460 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: all code categories | 1345 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench design | 82.1% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
| Benchmark | GPT-6.1 Sol | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Vals Index | 63.9% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench data analysis | 82.7% | Not measured | Only GPT-6.1 Sol measured |
| Public Benefits Bench (Vals AI) | 59.3% | Not measured | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | 46.5% | Not measured | Only GPT-6.1 Sol measured |
| MedScribe (Vals AI) | 86.5% | Not measured | Only GPT-6.1 Sol measured |
| Long context reasoning (AA-LCR) | 84.0% | Not measured | Only GPT-6.1 Sol measured |
| DTBench | 96.5% | Not measured | Only GPT-6.1 Sol measured |
| LMCA | 62.8% | Not measured | Only GPT-6.1 Sol measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text | 1443 | 1425 | GPT-6.1 Sol |
| LMArena Text: instruction following | 1466 | 1430 | GPT-6.1 Sol |
| LMArena Text: creative writing | 1425 | 1390 | GPT-6.1 Sol |
| LMArena Vision | 1288 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: English | 1450 | 1436 | GPT-6.1 Sol |
| LMArena Text: non-English | 1433 | 1413 | GPT-6.1 Sol |
| LMArena Text: Chinese | 1487 | 1424 | GPT-6.1 Sol |
| LMArena Text: French | 1460 | 1461 | Beam 1.0 501B A23B |
| LMArena Text: Spanish | 1439 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Russian | 1457 | 1412 | GPT-6.1 Sol |
| LMArena Text: multi-turn | 1442 | 1414 | GPT-6.1 Sol |
| LMArena Text: longer queries | 1458 | 1429 | GPT-6.1 Sol |
| LMArena Text: writing and language | 1444 | 1400 | GPT-6.1 Sol |
| LMArena Text: entertainment and media | 1426 | 1399 | GPT-6.1 Sol |
| LMArena Vision: English | 1274 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: reading text | 1289 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Sol | 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
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Beam 1.0 501B A23B 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-6.1 Sol | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | September 29, 2026 | October 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $0.35 |
| Output $/Mtok | $10.00 | $1.10 |
| Coding index | 82.4 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Sol better than Beam 1.0 501B A23B for coding?
Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Beam 1.0 501B A23B has none, so the two cannot be ranked on coding. Pick Beam 1.0 501B A23B for output tokens 9.1x cheaper ($1.10 vs $10.00 per million) and work measured by LMArena Text: French, where it leads.
Which is cheaper, GPT-6.1 Sol or Beam 1.0 501B A23B?
GPT-6.1 Sol costs $2.00 per million input tokens and $10.00 per million output tokens; Beam 1.0 501B A23B costs $0.35 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6.1 Sol or Beam 1.0 501B A23B?
GPT-6.1 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6.1 Sol vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. GPT-6.1 Sol's coding index rests on 5 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.