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GLM 5.1 vs Beam 1.0 501B A23B

Beam 1.0 501B A23B costs 4.0x less per output token than GLM 5.1 ($1.10 vs $4.40 per million). Updated October 22, 2026; 28 benchmarks have a result for both.

Replace GLM 5.1 Replace Beam 1.0 501B A23B
GLM 5.1Z.ai
Coding
49.2
Overall
57.5
Output $/M
$4.40
27
R Beam 1.0 501B A23BReflection
Coding
No data
Overall
No data
Output $/M
$1.10
1
vs boards won of 28 shared

GLM 5.1 or Beam 1.0 501B A23B: which to pick

Only GLM 5.1 has a coding score, 49.2 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 output tokens 4.0x cheaper ($1.10 vs $4.40 per million) and a larger context window (1.05M against 205K tokens).

Model AGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved taskModel BBeam 1.0 501B A23BReflectionNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
28
GLM 5.1 only
61
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
GLM 5.1 49.2 from 3 benchmarks, Beam 1.0 501B A23B not benchmarked.
Widest category
Knowledge, 8.3 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: medicine and healthcare: GLM 5.1 1474 against Beam 1.0 501B A23B 1376, 16.2 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against Beam 1.0 501B A23B $1.10 per million output tokens, 4.0x apart.
Context window
GLM 5.1 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
CategoryGLM 5.1BarsBeam 1.0 501B A23BTies
Coding50
Reasoning30
Math11
Knowledge40
Web design20
General120
All shared boards271
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
LMArena WebDev15081437GLM 5.1
AA Coding Index55.8Not measuredOnly GLM 5.1 measured
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly GLM 5.1 measured
Vibe Code Bench (Vals AI)31.5%Not measuredOnly GLM 5.1 measured
Code migration (Vals AI)25.8%Not measuredOnly GLM 5.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%Not measuredOnly GLM 5.1 measured
SciCode44.8%Not measuredOnly GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%Not measuredOnly GLM 5.1 measured
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1Not measuredOnly GLM 5.1 measured
LMArena Text: coding14851473GLM 5.1
LMArena Text: software and IT14841461GLM 5.1
LMArena WebDev: React15051443GLM 5.1
LMArena WebDev: HTML15081436GLM 5.1
Neither model has a result on the other 23 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
AA Intelligence Index26.1Not measuredOnly GLM 5.1 measured
Epoch Capabilities Index149.8Not measuredOnly GLM 5.1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
Agentic work benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
AA Agentic Index23.9Not measuredOnly GLM 5.1 measured
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1162Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1182Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1120Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1163Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%Not measuredOnly GLM 5.1 measured
Legal Research Bench (Vals AI)27.9%Not measuredOnly GLM 5.1 measured
τ²-Bench Telecom97.7%Not measuredOnly GLM 5.1 measured
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%Not measuredOnly GLM 5.1 measured
Humanity's Last Exam (Artificial Analysis run)30.1%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Epoch AI run)89.9%Not measuredOnly GLM 5.1 measured
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts14731442GLM 5.1
LMArena Text: expert14781447GLM 5.1
LMArena Text: hard prompts in English14821451GLM 5.1
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
AIME91.9%Not measuredOnly GLM 5.1 measured
OTIS Mock AIME93.3%Not measuredOnly GLM 5.1 measured
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math14731459GLM 5.1
LMArena Text: mathematical work14701475Beam 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 index40
Knowledge benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
MMLU Pro86.9%Not measuredOnly GLM 5.1 measured
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%Not measuredOnly GLM 5.1 measured
TaxEval (Vals AI)71.2%Not measuredOnly GLM 5.1 measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
SimpleQA Verified34.0%Not measuredOnly GLM 5.1 measured
LMArena Text: science14781430GLM 5.1
LMArena Text: medicine and healthcare14741376GLM 5.1
LMArena Text: legal and government14651433GLM 5.1
LMArena Text: business and finance14521430GLM 5.1
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index20
Web design benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
Design Arena: websites12901250GLM 5.1
Design Arena: UI components1292Not measuredOnly GLM 5.1 measured
Design Arena: game dev12651224GLM 5.1
Design Arena: data viz1366Not measuredOnly GLM 5.1 measured
Design Arena: 3D1336Not measuredOnly GLM 5.1 measured
Design Arena: all code categories1268Not measuredOnly GLM 5.1 measured
Design Arena: SVG1218Not measuredOnly GLM 5.1 measured
Design Arena: ASCII art1141Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 1.0 501B A23BLeader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
MedScribe (Vals AI)72.3%Not measuredOnly GLM 5.1 measured
IFBench76.3%Not measuredOnly GLM 5.1 measured
Long context reasoning (AA-LCR)73.7%Not measuredOnly GLM 5.1 measured
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631425GLM 5.1
LMArena Text: instruction following14531430GLM 5.1
LMArena Text: creative writing14531390GLM 5.1
LMArena Text: English14761436GLM 5.1
LMArena Text: non-English14481413GLM 5.1
LMArena Text: Chinese15151424GLM 5.1
LMArena Text: German1467Not measuredOnly GLM 5.1 measured
LMArena Text: Japanese1435Not measuredOnly GLM 5.1 measured
LMArena Text: Korean1424Not measuredOnly GLM 5.1 measured
LMArena Text: French14701461GLM 5.1
LMArena Text: Spanish1468Not measuredOnly GLM 5.1 measured
LMArena Text: Russian14541412GLM 5.1
LMArena Text: Polish1449Not measuredOnly GLM 5.1 measured
LMArena Text: multi-turn14731414GLM 5.1
LMArena Text: longer queries14671429GLM 5.1
LMArena Text: writing and language14541400GLM 5.1
LMArena Text: entertainment and media14421399GLM 5.1
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.1 and Beam 1.0 501B A23B
BenchmarkGLM 5.1Beam 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

GLM 5.1$0.0036Fits 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

GLM 5.1$0.083Fits 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

GLM 5.1$0.324Exceeds the context window
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.

Specifications of GLM 5.1 and Beam 1.0 501B A23B
SpecificationZ.ai GLM 5.1Reflection Beam 1.0 501B A23B
MakerZ.aiReflection
WeightsOpen weightsOpen weights
ReleasedApril 7, 2026October 16, 2026
Context window205K1.05M
Input $/Mtok$1.40$0.35
Output $/Mtok$4.40$1.10
Coding index49.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Beam 1.0 501B A23B for coding?

Only GLM 5.1 has a coding score, 49.2 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 output tokens 4.0x cheaper ($1.10 vs $4.40 per million) and a larger context window (1.05M against 205K tokens).

Which is cheaper, GLM 5.1 or Beam 1.0 501B A23B?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Beam 1.0 501B A23B costs $0.35 and $1.10. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or Beam 1.0 501B A23B?

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

How many benchmarks is the GLM 5.1 vs Beam 1.0 501B A23B comparison based on?

28 benchmarks have a result for both models as of October 22, 2026. GLM 5.1'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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