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Mercury 2 vs Beam 1.0 501B A23B

Updated October 21, 2026. 24 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Mercury 2Inception
Coding
0.0
Overall
10.8
Output $/M
$0.75
0
R Beam 1.0 501B A23BReflection
Coding
33.8
Overall
No data
Output $/M
$1.00
24
vs boards won of 24 shared

Decision reading

Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 0.0 for Mercury 2.

Pick Mercury 2 when output tokens cost 1.3x less.

Shared results
24
Mercury 2 only
18
Beam 1.0 501B A23B only
4
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
Mercury 2 0.0 from 1 benchmark, Beam 1.0 501B A23B 33.8 from 1 benchmark.
Widest category
Coding, 29.4 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena WebDev: React: Mercury 2 1160 against Beam 1.0 501B A23B 1443, 47.1 points apart on a 0 to 100 scale.
Output price
Mercury 2 $0.75 against Beam 1.0 501B A23B $1.00 per million output tokens, 1.3x apart.
Context window
Mercury 2 takes 128K 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.

Boards won, where both have a result
CategoryMercury 2BarsBeam 1.0 501B A23BTies
Coding05
Reasoning03
Knowledge03
Web design02
General011
All shared boards024
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
Coding benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
LMArena WebDev11711437Beam 1.0 501B A23B
AA Coding Index31.1Not measuredOnly Mercury 2 measured
SciCode37.7%Not measuredOnly Mercury 2 measured
Terminal-Bench Hard (Artificial Analysis run)26.5%Not measuredOnly Mercury 2 measured
WeirdML43.2%Not measuredOnly Mercury 2 measured
ALE-Bench785.6Not measuredOnly Mercury 2 measured
LMArena Text: coding13901473Beam 1.0 501B A23B
LMArena Text: software and IT13851461Beam 1.0 501B A23B
LMArena WebDev: React11601443Beam 1.0 501B A23B
LMArena WebDev: HTML11991436Beam 1.0 501B A23B
Neither model has a result on the other 28 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
AA Intelligence Index10.8Not measuredOnly Mercury 2 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
AA Agentic Index1.6Not measuredOnly Mercury 2 measured
τ²-Bench Telecom70.8%Not measuredOnly Mercury 2 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
GPQA Diamond (Artificial Analysis run)77.0%Not measuredOnly Mercury 2 measured
Humanity's Last Exam (Artificial Analysis run)17.1%Not measuredOnly Mercury 2 measured
LMArena Text: hard prompts13621442Beam 1.0 501B A23B
LMArena Text: expert13581447Beam 1.0 501B A23B
LMArena Text: hard prompts in English13741451Beam 1.0 501B A23B
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
LMArena Text: mathNot measured1459Only Beam 1.0 501B A23B measured
LMArena Text: mathematical workNot measured1475Only Beam 1.0 501B A23B measured
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
Knowledge benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
LMArena Text: science13431430Beam 1.0 501B A23B
LMArena Text: medicine and healthcare13631376Beam 1.0 501B A23B
LMArena Text: legal and governmentNot measured1433Only Beam 1.0 501B A23B measured
LMArena Text: business and finance13491430Beam 1.0 501B A23B
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index02
Web design benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
Design Arena: websites10361253Beam 1.0 501B A23B
Design Arena: UI components998Not measuredOnly Mercury 2 measured
Design Arena: game dev9851222Beam 1.0 501B A23B
Design Arena: data viz1009Not measuredOnly Mercury 2 measured
Design Arena: 3D982Not measuredOnly Mercury 2 measured
Design Arena: all code categories1022Not measuredOnly Mercury 2 measured
Design Arena: SVG998Not measuredOnly Mercury 2 measured
Design Arena: ASCII art990Not measuredOnly Mercury 2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index011
General benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
IFBench69.8%Not measuredOnly Mercury 2 measured
Long context reasoning (AA-LCR)43.7%Not measuredOnly Mercury 2 measured
LMArena Text13541425Beam 1.0 501B A23B
LMArena Text: instruction following13281430Beam 1.0 501B A23B
LMArena Text: creative writing12861390Beam 1.0 501B A23B
LMArena Text: English13781436Beam 1.0 501B A23B
LMArena Text: non-English13301413Beam 1.0 501B A23B
LMArena Text: Chinese14141424Beam 1.0 501B A23B
LMArena Text: FrenchNot measured1461Only Beam 1.0 501B A23B measured
LMArena Text: Russian13041412Beam 1.0 501B A23B
LMArena Text: multi-turn13571414Beam 1.0 501B A23B
LMArena Text: longer queries13291429Beam 1.0 501B A23B
LMArena Text: writing and language13001400Beam 1.0 501B A23B
LMArena Text: entertainment and media13141399Beam 1.0 501B A23B
Neither model has a result on the other 32 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mercury 2 and Beam 1.0 501B A23B
BenchmarkMercury 2Beam 1.0 501B A23BLeader
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

Mercury 2$0.0006Fits in one request
Beam 1.0 501B A23B$0.0008Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

Mercury 2$0.015Fits in one request
Beam 1.0 501B A23B$0.018Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

Mercury 2$0.058Exceeds the context window
Beam 1.0 501B A23B$0.070Fits in one request

Mercury 2 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 Mercury 2 and Beam 1.0 501B A23B
SpecificationInception Mercury 2Reflection Beam 1.0 501B A23B
MakerInceptionReflection
WeightsNo public weights listedOpen weights
ReleasedMarch 4, 2026October 16, 2026
Context window128K1.05M
Input $/Mtok$0.25$0.30
Output $/Mtok$0.75$1.00
Coding index0.033.8
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2 better than Beam 1.0 501B A23B for coding?

Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 0.0 for Mercury 2. Pick Mercury 2 when output tokens cost 1.3x less.

Which is cheaper, Mercury 2 or Beam 1.0 501B A23B?

Mercury 2 costs $0.25 per million input tokens and $0.75 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, Mercury 2 or Beam 1.0 501B A23B?

Beam 1.0 501B A23B, with 1.05M tokens against 128K.

How many benchmarks is the Mercury 2 vs Beam 1.0 501B A23B comparison based on?

24 benchmarks have a result for both models as of October 21, 2026. Mercury 2's coding index rests on 1 independent benchmark 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.

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