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Beam 1.0 501B A23B vs Step 5 Preview

Updated October 21, 2026. 26 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

R Beam 1.0 501B A23BReflection
Coding
33.8
Overall
No data
Output $/M
$1.00
3
Step 5 PreviewStepFun
Coding
71.4
Overall
43.7
Output $/M
$2.70
23
vs boards won of 26 shared

Decision reading

Pick Step 5 Preview 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 output tokens cost 2.7x less, or when what matters is LMArena Text: math or LMArena Text: mathematical work, where it leads.

Shared results
26
Beam 1.0 501B A23B only
2
Step 5 Preview only
35
Like-for-like categories
5 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.

At a glance

Coding index
Beam 1.0 501B A23B 33.8 from 1 benchmark, Step 5 Preview 71.4 from 2 benchmarks.
Widest category
Coding, 13.2 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena WebDev: React: Beam 1.0 501B A23B 1443 against Step 5 Preview 1583, 23.4 points apart on a 0 to 100 scale.
Output price
Beam 1.0 501B A23B $1.00 against Step 5 Preview $2.70 per million output tokens, 2.7x apart.
Context window
Both take 1.05M tokens.

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.

Boards won, where both have a result
CategoryBeam 1.0 501B A23BBarsStep 5 PreviewTies
Coding05
Reasoning03
Math20
Knowledge04
General111
All shared boards323
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
Coding benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
LiveBench codingNot measured85.6%Only Step 5 Preview measured
LMArena WebDev14371567Step 5 Preview
Terminal-Bench 4 (Vals AI)Not measured31.8%Only Step 5 Preview measured
Vibe Code Bench (Vals AI)Not measured70.4%Only Step 5 Preview measured
Code migration (Vals AI)Not measured39.0%Only Step 5 Preview measured
IOI (Vals AI)Not measured38.1%Only Step 5 Preview measured
SWE-bench Multimodal (Vals AI)Not measured40.8%Only Step 5 Preview measured
SciCodeNot measured58.9%Only Step 5 Preview measured
LMArena Text: coding14731485Step 5 Preview
LMArena Text: software and IT14611473Step 5 Preview
LMArena WebDev: React14431583Step 5 Preview
LMArena WebDev: HTML14361556Step 5 Preview
LMArena WebDev: from an imageNot measured1550Only Step 5 Preview measured
Neither model has a result on the other 25 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
AA Intelligence IndexNot measured43.7Only Step 5 Preview measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Agentic work benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
LiveBench researchNot measured72.8%Only Step 5 Preview measured
LiveBench browserNot measured24.0%Only Step 5 Preview measured
LiveBench long agenticNot measured27.5%Only Step 5 Preview measured
SREBench (Vals AI)Not measured0.4%Only Step 5 Preview measured
Finance Agent (Vals AI)Not measured50.7%Only Step 5 Preview measured
Tax Agent Bench (Vals AI)Not measured27.3%Only Step 5 Preview measured
Legal Research Bench (Vals AI)Not measured40.4%Only Step 5 Preview measured
Excel Modeling Benchmark (Vals AI)Not measured57.1%Only Step 5 Preview measured
BioMysteryBench (Vals AI)Not measured67.4%Only Step 5 Preview measured
Terminal-Bench-Science (Vals AI)Not measured2.9%Only Step 5 Preview measured
Vals Science IndexNot measured29.6%Only Step 5 Preview measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
LiveBench reasoningNot measured83.8%Only Step 5 Preview measured
MysteryMechanism (Vals AI)Not measured18.5%Only Step 5 Preview measured
Humanity's Last Exam (Artificial Analysis run)Not measured46.5%Only Step 5 Preview measured
LMArena Text: hard prompts14421461Step 5 Preview
LMArena Text: expert14471485Step 5 Preview
LMArena Text: hard prompts in English14511454Step 5 Preview
LMArena Vision: diagramsNot measured1308Only Step 5 Preview measured
LMArena Vision: homeworkNot measured1265Only Step 5 Preview measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
ProofBenchNot measured42.0%Only Step 5 Preview measured
LMArena Text: math14591458Beam 1.0 501B A23B
LMArena Text: mathematical work14751460Beam 1.0 501B A23B
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
LMArena Text: science14301454Step 5 Preview
LMArena Text: medicine and healthcare13761439Step 5 Preview
LMArena Text: legal and government14331437Step 5 Preview
LMArena Text: business and finance14301435Step 5 Preview
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Web design benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
Design Arena: websites1253Not measuredOnly Beam 1.0 501B A23B measured
Design Arena: game dev1222Not measuredOnly Beam 1.0 501B A23B measured
LiveBench designNot measured76.9%Only Step 5 Preview measured
Neither model has a result on the other 6 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
General benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
LiveBench data analysisNot measured63.5%Only Step 5 Preview measured
Public Benefits Bench (Vals AI)Not measured58.1%Only Step 5 Preview measured
Long context reasoning (AA-LCR)Not measured88.3%Only Step 5 Preview measured
LMArena Text14251440Step 5 Preview
LMArena Text: instruction following14301438Step 5 Preview
LMArena Text: creative writing13901409Step 5 Preview
LMArena VisionNot measured1265Only Step 5 Preview measured
LMArena Text: English14361447Step 5 Preview
LMArena Text: non-English14131428Step 5 Preview
LMArena Text: Chinese14241500Step 5 Preview
LMArena Text: JapaneseNot measured1383Only Step 5 Preview measured
LMArena Text: French14611438Beam 1.0 501B A23B
LMArena Text: SpanishNot measured1441Only Step 5 Preview measured
LMArena Text: Russian14121433Step 5 Preview
LMArena Text: multi-turn14141437Step 5 Preview
LMArena Text: longer queries14291449Step 5 Preview
LMArena Text: writing and language14001425Step 5 Preview
LMArena Text: entertainment and media13991412Step 5 Preview
LMArena Vision: EnglishNot measured1290Only Step 5 Preview measured
LMArena Vision: reading textNot measured1282Only Step 5 Preview measured
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Beam 1.0 501B A23B and Step 5 Preview
BenchmarkBeam 1.0 501B A23BStep 5 PreviewLeader
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$0.0008Fits in one request
Step 5 Preview$0.0024Fits in one request

Beam 1.0 501B A23B costs less

Repository review

50K input + 3K output tokens

Beam 1.0 501B A23B$0.018Fits in one request
Step 5 Preview$0.058Fits in one request

Beam 1.0 501B A23B costs less

Agent loop

200K input + 10K output tokens

Beam 1.0 501B A23B$0.070Fits in one request
Step 5 Preview$0.227Fits 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.

Specifications of Beam 1.0 501B A23B and Step 5 Preview
SpecificationReflection Beam 1.0 501B A23BStepFun Step 5 Preview
MakerReflectionStepFun
WeightsOpen weightsOpen weights
ReleasedOctober 16, 2026October 8, 2026
Context window1.05M1.05M
Input $/Mtok$0.30$1.00
Output $/Mtok$1.00$2.70
Coding index33.871.4
Independent measurements behind it12
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Beam 1.0 501B A23B better than Step 5 Preview for coding?

Pick Step 5 Preview 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 output tokens cost 2.7x less, or when what matters is LMArena Text: math or LMArena Text: mathematical work, where it leads.

Which is cheaper, Beam 1.0 501B A23B or Step 5 Preview?

Beam 1.0 501B A23B costs $0.30 per million input tokens and $1.00 per million output tokens; Step 5 Preview costs $1.00 and $2.70. Cost per solved task is known for neither of them.

Which has the bigger context window, Beam 1.0 501B A23B or Step 5 Preview?

Neither: both take 1.05M tokens.

How many benchmarks is the Beam 1.0 501B A23B vs Step 5 Preview comparison based on?

26 benchmarks have a result for both models as of October 21, 2026. Beam 1.0 501B A23B's coding index rests on 1 independent benchmark and Step 5 Preview's on 2. Where only one model has a result, the page says so instead of naming a winner.

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