GPT-5.6 Terra vs Beam 1.0 501B A23B
Beam 1.0 501B A23B costs 10.9x less per output token than GPT-5.6 Terra ($1.10 vs $12.00 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
vs boards won of 28 shared
GPT-5.6 Terra or Beam 1.0 501B A23B: which to pick
Only GPT-5.6 Terra has a coding score, 63.9 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 10.9x cheaper ($1.10 vs $12.00 per million).
Model AGPT-5.6 TerraOpenAI63.9/1006 independent benchmarks$0.42 per solved taskModel BBeam 1.0 501B A23BReflectionNot benchmarked1 independent benchmarkNo cost per solved task
- Shared results
- 28
- GPT-5.6 Terra only
- 99
- 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-5.6 Terra has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.6 Terra has a AA Intelligence Index result, 42.1.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Terra has a AA Agentic Index result, 43.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Terra has a GPQA Diamond result, 90.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Terra has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Terra
GPT-5.6 Terra leads, 1268 against 1250.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
GPT-5.6 Terra $0.0080, Beam 1.0 501B A23B $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Terra has the number, $0.42.
Directional only
At a glance
- Coding index
- GPT-5.6 Terra 63.9 from 6 benchmarks, Beam 1.0 501B A23B not benchmarked.
- Widest category
- Coding, 8.9 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: GPT-5.6 Terra 1526 against Beam 1.0 501B A23B 1436, 15.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Terra $12.00 against Beam 1.0 501B A23B $1.10 per million output tokens, 10.9x apart.
- Context window
- GPT-5.6 Terra 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-5.6 Terra | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 2 | 0 | ||
| General | 12 | 0 | ||
| All shared boards | 28 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench coding | 86.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev | 1522 | 1437 | GPT-5.6 Terra |
| AA Coding Index | 76.7 | Not measured | Only GPT-5.6 Terra measured |
| LiveCodeBench (Vals AI) | 85.9% | Not measured | Only GPT-5.6 Terra measured |
| SWE-bench Verified (Vals AI) | 95.4% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench 4 (Vals AI) | 22.7% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench (Vals AI) | 74.6% | Not measured | Only GPT-5.6 Terra measured |
| Code migration (Vals AI) | 47.8% | Not measured | Only GPT-5.6 Terra measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.6 Terra measured |
| IOI (Vals AI) | 87.6% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.8% | Not measured | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | 58.9% | Not measured | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 55.0% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | Not measured | Only GPT-5.6 Terra measured |
| FrontierCode | 41.3% | Not measured | Only GPT-5.6 Terra measured |
| WeirdML | 78.3% | Not measured | Only GPT-5.6 Terra measured |
| ALE-Bench | 1951.4 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: coding | 1485 | 1473 | GPT-5.6 Terra |
| LMArena Text: software and IT | 1482 | 1461 | GPT-5.6 Terra |
| LMArena WebDev: React | 1513 | 1443 | GPT-5.6 Terra |
| LMArena WebDev: HTML | 1526 | 1436 | GPT-5.6 Terra |
| LMArena WebDev: from an image | 1541 | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 10.8% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.1 | Not measured | Only GPT-5.6 Terra measured |
| Epoch Capabilities Index | 160.1 | Not measured | Only GPT-5.6 Terra measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Agentic Index | 43.2 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building web apps | 1120 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | 1061 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | 1111 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | 1062 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | 1083 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | 1058 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | 1105 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench research | 60.4% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench browser | 84.0% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench long agentic | 48.4% | Not measured | Only GPT-5.6 Terra measured |
| SREBench (Vals AI) | 9.5% | Not measured | Only GPT-5.6 Terra measured |
| Finance Agent (Vals AI) | 54.4% | Not measured | Only GPT-5.6 Terra measured |
| Tax Agent Bench (Vals AI) | 30.0% | Not measured | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only GPT-5.6 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 66.2% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | 86.3% | Not measured | Only GPT-5.6 Terra measured |
| APEX-Agents | 58.2% | Not measured | Only GPT-5.6 Terra measured |
| BALROG | 53.2% | Not measured | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | $7,343 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond | 90.9% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench reasoning | 90.6% | Not measured | Only GPT-5.6 Terra measured |
| MMMU Pro (Vals AI) | 86.5% | Not measured | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 92.5% | Not measured | Only GPT-5.6 Terra measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.9% | Not measured | Only GPT-5.6 Terra measured |
| GPQA Diamond (Epoch AI run) | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI | 96.5% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI-2 | 83.9% | Not measured | Only GPT-5.6 Terra measured |
| SimpleBench | 48.9% | Not measured | Only GPT-5.6 Terra measured |
| Chess puzzles | 47.0% | Not measured | Only GPT-5.6 Terra measured |
| Mystery game puzzles | 35.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts | 1469 | 1442 | GPT-5.6 Terra |
| LMArena Text: expert | 1496 | 1447 | GPT-5.6 Terra |
| LMArena Text: hard prompts in English | 1465 | 1451 | GPT-5.6 Terra |
| LMArena Vision: diagrams | 1295 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: homework | 1312 | Not measured | Only GPT-5.6 Terra measured |
| Kagi LLM Benchmark | 51.3% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 99.7% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tiers 1 to 3 | 86.0% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | 70.7% | Not measured | Only GPT-5.6 Terra measured |
| ProofBench | 74.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: math | 1465 | 1459 | GPT-5.6 Terra |
| LMArena Text: mathematical work | 1478 | 1475 | GPT-5.6 Terra |
| 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-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | Not measured | Only GPT-5.6 Terra measured |
| LegalBench (Vals AI) | 85.1% | Not measured | Only GPT-5.6 Terra measured |
| CorpFin (Vals AI) | 65.3% | Not measured | Only GPT-5.6 Terra measured |
| TaxEval (Vals AI) | 76.2% | Not measured | Only GPT-5.6 Terra measured |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Terra measured |
| MedCode (Vals AI) | 43.4% | Not measured | Only GPT-5.6 Terra measured |
| SimpleQA Verified | 43.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: science | 1452 | 1430 | GPT-5.6 Terra |
| LMArena Text: medicine and healthcare | 1430 | 1376 | GPT-5.6 Terra |
| LMArena Text: legal and government | 1461 | 1433 | GPT-5.6 Terra |
| LMArena Text: business and finance | 1448 | 1430 | GPT-5.6 Terra |
| FACTS Benchmark Suite | 52.0% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | 1250 | GPT-5.6 Terra |
| Design Arena: UI components | 1256 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: game dev | 1229 | 1224 | GPT-5.6 Terra |
| Design Arena: data viz | 1240 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: 3D | 1134 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: all code categories | 1241 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: SVG | 1219 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: ASCII art | 1177 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
| Benchmark | GPT-5.6 Terra | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only GPT-5.6 Terra measured |
| Public Benefits Bench (Vals AI) | 62.4% | Not measured | Only GPT-5.6 Terra measured |
| SAGE (Vals AI) | 47.0% | Not measured | Only GPT-5.6 Terra measured |
| MedScribe (Vals AI) | 82.9% | Not measured | Only GPT-5.6 Terra measured |
| Vals Multimodal Index | 65.1% | Not measured | Only GPT-5.6 Terra measured |
| IFBench | 71.2% | Not measured | Only GPT-5.6 Terra measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only GPT-5.6 Terra measured |
| DTBench | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| LMCA | 54.9% | Not measured | Only GPT-5.6 Terra measured |
| Surface Evolver Bench | 83.8% | Not measured | Only GPT-5.6 Terra measured |
| Furniture assembly | 54.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text | 1448 | 1425 | GPT-5.6 Terra |
| LMArena Text: instruction following | 1456 | 1430 | GPT-5.6 Terra |
| LMArena Text: creative writing | 1413 | 1390 | GPT-5.6 Terra |
| LMArena Vision | 1271 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: English | 1449 | 1436 | GPT-5.6 Terra |
| LMArena Text: non-English | 1441 | 1413 | GPT-5.6 Terra |
| LMArena Text: Chinese | 1514 | 1424 | GPT-5.6 Terra |
| LMArena Text: German | 1460 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | 1454 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | 1427 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: French | 1466 | 1461 | GPT-5.6 Terra |
| LMArena Text: Spanish | 1451 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Russian | 1452 | 1412 | GPT-5.6 Terra |
| LMArena Text: Polish | 1446 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | 1453 | 1414 | GPT-5.6 Terra |
| LMArena Text: longer queries | 1454 | 1429 | GPT-5.6 Terra |
| LMArena Text: writing and language | 1431 | 1400 | GPT-5.6 Terra |
| LMArena Text: entertainment and media | 1418 | 1399 | GPT-5.6 Terra |
| LMArena Vision: English | 1272 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: Chinese | 1337 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | 1278 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: humor | 1236 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | 1248 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Document | 1472 | Not measured | Only GPT-5.6 Terra 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 Terra | 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-5.6 Terra$0.0080Fits in one request
Beam 1.0 501B A23B$0.0009Fits in one request
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Terra$0.136Fits in one request
Beam 1.0 501B A23B$0.021Fits in one request
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Terra$0.520Fits in one request
Beam 1.0 501B A23B$0.081Fits in one request
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-5.6 Terra | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | October 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $0.35 |
| Output $/Mtok | $12.00 | $1.10 |
| Coding index | 63.9 | Not benchmarked |
| Independent measurements behind it | 6 | 1 |
| Cost per solved task | $0.42 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Terra better than Beam 1.0 501B A23B for coding?
Only GPT-5.6 Terra has a coding score, 63.9 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 10.9x cheaper ($1.10 vs $12.00 per million).
Which is cheaper, GPT-5.6 Terra or Beam 1.0 501B A23B?
GPT-5.6 Terra costs $2.00 per million input tokens and $12.00 per million output tokens; Beam 1.0 501B A23B costs $0.35 and $1.10. Cost per solved task is known for GPT-5.6 Terra only.
Which has the bigger context window, GPT-5.6 Terra or Beam 1.0 501B A23B?
GPT-5.6 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.6 Terra vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Terra's coding index rests on 6 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.