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MiniMax M2.7 vs Beam 1.0 501B A23B

MiniMax M2.7 and Beam 1.0 501B A23B cost about the same per output token ($1.20 vs $1.20 per million). Updated October 22, 2026; 28 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Beam 1.0 501B A23B
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
2
R Beam 1.0 501B A23BReflection
Coding
No data
Overall
No data
Output $/M
$1.20
26
vs boards won of 28 shared

MiniMax M2.7 or Beam 1.0 501B A23B: which to pick

Only MiniMax M2.7 has a coding score, 36.2 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 a larger context window (1.05M against 205K tokens) and work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BBeam 1.0 501B A23BReflectionNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
28
MiniMax M2.7 only
46
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.

At a glance

Coding index
MiniMax M2.7 36.2 from 3 benchmarks, Beam 1.0 501B A23B not benchmarked.
Widest category
Math, 6.3 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena WebDev: React: MiniMax M2.7 1388 against Beam 1.0 501B A23B 1443, 9.1 points apart on a 0 to 100 scale.
Output price
Both cost $1.20 per million output tokens.
Context window
MiniMax M2.7 takes 205K 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
CategoryMiniMax M2.7BarsBeam 1.0 501B A23BTies
Coding05
Reasoning03
Math02
Knowledge13
Web design02
General111
All shared boards226
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
LMArena WebDev13991437Beam 1.0 501B A23B
AA Coding Index52.6Not measuredOnly MiniMax M2.7 measured
LiveCodeBench (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
SWE-bench Verified (Vals AI)73.8%Not measuredOnly MiniMax M2.7 measured
Vibe Code Bench (Vals AI)11.9%Not measuredOnly MiniMax M2.7 measured
Code migration (Vals AI)8.7%Not measuredOnly MiniMax M2.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)48.7%Not measuredOnly MiniMax M2.7 measured
SciCode50.1%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)39.4%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3Not measuredOnly MiniMax M2.7 measured
LMArena Text: coding14541473Beam 1.0 501B A23B
LMArena Text: software and IT14461461Beam 1.0 501B A23B
LMArena WebDev: React13881443Beam 1.0 501B A23B
LMArena WebDev: HTML14011436Beam 1.0 501B A23B
Neither model has a result on the other 26 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
AA Intelligence Index22.8Not measuredOnly MiniMax M2.7 measured
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
AA Agentic Index15.3Not measuredOnly MiniMax M2.7 measured
Finance Agent (Vals AI)27.9%Not measuredOnly MiniMax M2.7 measured
Tax Agent Bench (Vals AI)6.9%Not measuredOnly MiniMax M2.7 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)28.4%Not measuredOnly MiniMax M2.7 measured
τ²-Bench Telecom84.8%Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)87.4%Not measuredOnly MiniMax M2.7 measured
Humanity's Last Exam (Artificial Analysis run)29.6%Not measuredOnly MiniMax M2.7 measured
LMArena Text: hard prompts14221442Beam 1.0 501B A23B
LMArena Text: expert14431447Beam 1.0 501B A23B
LMArena Text: hard prompts in English14411451Beam 1.0 501B A23B
Neither model has a result on the other 17 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211459Beam 1.0 501B A23B
LMArena Text: mathematical work14371475Beam 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 index13
Knowledge benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
MMLU Pro80.4%Not measuredOnly MiniMax M2.7 measured
LegalBench (Vals AI)84.0%Not measuredOnly MiniMax M2.7 measured
CaseLaw (Vals AI)60.9%Not measuredOnly MiniMax M2.7 measured
CorpFin (Vals AI)61.2%Not measuredOnly MiniMax M2.7 measured
TaxEval (Vals AI)66.6%Not measuredOnly MiniMax M2.7 measured
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
LMArena Text: science14161430Beam 1.0 501B A23B
LMArena Text: medicine and healthcare14091376MiniMax M2.7
LMArena Text: legal and government14031433Beam 1.0 501B A23B
LMArena Text: business and finance14071430Beam 1.0 501B A23B
Neither model has a result on the other 10 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index02
Web design benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
Design Arena: websites12421245Beam 1.0 501B A23B
Design Arena: UI components1207Not measuredOnly MiniMax M2.7 measured
Design Arena: game dev12091220Beam 1.0 501B A23B
Design Arena: data viz1233Not measuredOnly MiniMax M2.7 measured
Design Arena: 3D1194Not measuredOnly MiniMax M2.7 measured
Design Arena: all code categories1233Not measuredOnly MiniMax M2.7 measured
Design Arena: SVG1137Not measuredOnly MiniMax M2.7 measured
Design Arena: ASCII art1136Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
General benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 1.0 501B A23BLeader
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
IFBench75.7%Not measuredOnly MiniMax M2.7 measured
Long context reasoning (AA-LCR)78.3%Not measuredOnly MiniMax M2.7 measured
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051425Beam 1.0 501B A23B
LMArena Text: instruction following14051430Beam 1.0 501B A23B
LMArena Text: creative writing13541390Beam 1.0 501B A23B
LMArena Text: English14261436Beam 1.0 501B A23B
LMArena Text: non-English13821413Beam 1.0 501B A23B
LMArena Text: Chinese14421424MiniMax M2.7
LMArena Text: German1398Not measuredOnly MiniMax M2.7 measured
LMArena Text: Japanese1260Not measuredOnly MiniMax M2.7 measured
LMArena Text: Korean1314Not measuredOnly MiniMax M2.7 measured
LMArena Text: French14241461Beam 1.0 501B A23B
LMArena Text: Spanish1402Not measuredOnly MiniMax M2.7 measured
LMArena Text: Russian13831412Beam 1.0 501B A23B
LMArena Text: Polish1387Not measuredOnly MiniMax M2.7 measured
LMArena Text: multi-turn14121414Beam 1.0 501B A23B
LMArena Text: longer queries14181429Beam 1.0 501B A23B
LMArena Text: writing and language13761400Beam 1.0 501B A23B
LMArena Text: entertainment and media13601399Beam 1.0 501B A23B
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M2.7 and Beam 1.0 501B A23B
BenchmarkMiniMax M2.7Beam 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

MiniMax M2.7$0.0009Fits in one request
Beam 1.0 501B A23B$0.0010Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Beam 1.0 501B A23B$0.024Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Beam 1.0 501B A23B$0.092Fits in one request

MiniMax M2.7 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 MiniMax M2.7 and Beam 1.0 501B A23B
SpecificationMiniMax M2.7Reflection Beam 1.0 501B A23B
MakerMiniMaxReflection
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026October 16, 2026
Context window205K1.05M
Input $/Mtok$0.30$0.40
Output $/Mtok$1.20$1.20
Coding index36.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Beam 1.0 501B A23B for coding?

Only MiniMax M2.7 has a coding score, 36.2 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 a larger context window (1.05M against 205K tokens) and work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Which is cheaper, MiniMax M2.7 or Beam 1.0 501B A23B?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Beam 1.0 501B A23B costs $0.40 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Beam 1.0 501B A23B?

Beam 1.0 501B A23B, with 1.05M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Beam 1.0 501B A23B comparison based on?

28 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 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.

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