GPT-5.4 Nano vs Beam 1.0 501B A23B
GPT-5.4 Nano and Beam 1.0 501B A23B cost about the same per output token ($1.25 vs $1.20 per million). Updated October 23, 2026; 23 benchmarks have a result for both.
GPT-5.4 Nano or Beam 1.0 501B A23B: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 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 1.0x cheaper ($1.20 vs $1.25 per million) and a larger context window (1.05M against 400K tokens).
- Shared results
- 23
- GPT-5.4 Nano only
- 62
- Beam 1.0 501B A23B only
- 5
- Like-for-like categories
- 5 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-5.4 Nano has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.4 Nano has a AA Intelligence Index result, 20.7.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Nano has a GPQA Diamond result, 77.5%.
Directional only
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Nano has a MMLU Pro result, 77.2%.
Directional only
Web design
Design Arena: websites
No call
Only Beam 1.0 501B A23B has a Design Arena: websites result, 1247.
Directional only
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5.4 Nano $0.0008, Beam 1.0 501B A23B $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Nano has the number, $0.14.
Directional only
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, Beam 1.0 501B A23B not benchmarked.
- Widest category
- Coding, 10.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: GPT-5.4 Nano 1314 against Beam 1.0 501B A23B 1391, 12.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Beam 1.0 501B A23B $1.20 per million output tokens, 1.0x apart.
- Context window
- GPT-5.4 Nano takes 400K 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-5.4 Nano | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 12 | ||
| All shared boards | 0 | 23 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only GPT-5.4 Nano measured |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.4 Nano measured |
| Vibe Code Bench (Vals AI) | 26.1% | Not measured | Only GPT-5.4 Nano measured |
| Code migration (Vals AI) | 14.5% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | Not measured | Only GPT-5.4 Nano measured |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only GPT-5.4 Nano measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: coding | 1405 | 1472 | Beam 1.0 501B A23B |
| LMArena Text: software and IT | 1403 | 1461 | Beam 1.0 501B A23B |
| LMArena WebDev: React | Not measured | 1441 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: HTML | Not measured | 1438 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | Not measured | Only GPT-5.4 Nano measured |
| Epoch Capabilities Index | 146.0 | Not measured | Only GPT-5.4 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | Not measured | Only GPT-5.4 Nano measured |
| Finance Agent (Vals AI) | 38.2% | Not measured | Only GPT-5.4 Nano measured |
| Tax Agent Bench (Vals AI) | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| Legal Research Bench (Vals AI) | 6.3% | Not measured | Only GPT-5.4 Nano measured |
| Excel Modeling Benchmark (Vals AI) | 44.8% | Not measured | Only GPT-5.4 Nano measured |
| τ²-Bench Telecom | 76.0% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | Not measured | Only GPT-5.4 Nano measured |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | Not measured | Only GPT-5.4 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Epoch AI run) | 78.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI | 51.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI-2 | 5.7% | Not measured | Only GPT-5.4 Nano measured |
| Chess puzzles | 45.0% | Not measured | Only GPT-5.4 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts | 1381 | 1442 | Beam 1.0 501B A23B |
| LMArena Text: expert | 1396 | 1447 | Beam 1.0 501B A23B |
| LMArena Text: hard prompts in English | 1387 | 1452 | Beam 1.0 501B A23B |
| LMArena Vision: diagrams | 1210 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | 1225 | Not measured | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | 39.7% | Not measured | Only GPT-5.4 Nano 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-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 87.8% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tiers 1 to 3 | 44.9% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5.4 Nano measured |
| ProofBench | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: math | 1406 | 1460 | Beam 1.0 501B A23B |
| LMArena Text: mathematical work | 1409 | 1474 | 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-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-5.4 Nano measured |
| LegalBench (Vals AI) | 77.9% | Not measured | Only GPT-5.4 Nano measured |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only GPT-5.4 Nano measured |
| TaxEval (Vals AI) | 67.4% | Not measured | Only GPT-5.4 Nano measured |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | Not measured | Only GPT-5.4 Nano measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | 1431 | Beam 1.0 501B A23B |
| LMArena Text: medicine and healthcare | 1369 | 1378 | Beam 1.0 501B A23B |
| LMArena Text: legal and government | 1368 | 1431 | Beam 1.0 501B A23B |
| LMArena Text: business and finance | 1366 | 1430 | Beam 1.0 501B A23B |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1247 | Only Beam 1.0 501B A23B measured |
| Design Arena: game dev | Not measured | 1212 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 7 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
| Benchmark | GPT-5.4 Nano | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | Not measured | Only GPT-5.4 Nano measured |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | Not measured | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 76.7% | Not measured | Only GPT-5.4 Nano measured |
| DTBench | 80.3% | Not measured | Only GPT-5.4 Nano measured |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | 1426 | Beam 1.0 501B A23B |
| LMArena Text: instruction following | 1362 | 1431 | Beam 1.0 501B A23B |
| LMArena Text: creative writing | 1314 | 1391 | Beam 1.0 501B A23B |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | 1437 | Beam 1.0 501B A23B |
| LMArena Text: non-English | 1360 | 1412 | Beam 1.0 501B A23B |
| LMArena Text: Chinese | 1391 | 1428 | Beam 1.0 501B A23B |
| LMArena Text: German | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | 1343 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | 1320 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: French | 1395 | 1461 | Beam 1.0 501B A23B |
| LMArena Text: Spanish | 1371 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | 1362 | 1411 | Beam 1.0 501B A23B |
| LMArena Text: Polish | 1366 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | 1382 | 1416 | Beam 1.0 501B A23B |
| LMArena Text: longer queries | 1366 | 1429 | Beam 1.0 501B A23B |
| LMArena Text: writing and language | 1338 | 1401 | Beam 1.0 501B A23B |
| LMArena Text: entertainment and media | 1324 | 1400 | Beam 1.0 501B A23B |
| LMArena Vision: English | 1202 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | 1232 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | 1204 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | 1161 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | 1159 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | 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-5.4 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Nano 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-5.4 Nano | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | October 16, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $0.20 | $0.40 |
| Output $/Mtok | $1.25 | $1.20 |
| Coding index | 44.8 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.14 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than Beam 1.0 501B A23B for coding?
Only GPT-5.4 Nano has a coding score, 44.8 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 1.0x cheaper ($1.20 vs $1.25 per million) and a larger context window (1.05M against 400K tokens).
Which is cheaper, GPT-5.4 Nano or Beam 1.0 501B A23B?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Beam 1.0 501B A23B costs $0.40 and $1.20. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.4 Nano vs Beam 1.0 501B A23B comparison based on?
23 benchmarks have a result for both models as of October 23, 2026. GPT-5.4 Nano'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.