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GLM 5.1 vs Grok 4.20 Multi-Agent

Grok 4.20 Multi-Agent costs 1.8x less per output token than GLM 5.1 ($2.50 vs $4.40 per million). Updated October 21, 2026; no benchmark has tested both models yet.

GLM 5.1Z.ai
Coding
49.2
Overall
26.1
Output $/M
$4.40
Grok 4.20 Multi-AgentxAI
Coding
No data
Overall
No data
Output $/M
$2.50
vs $4.40 vs $2.50 per 1M output tokens. Grok 4.20 Multi-Agent is 1.8x cheaper.

GLM 5.1 or Grok 4.20 Multi-Agent: which to pick

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Grok 4.20 Multi-Agent has none, so the two cannot be ranked on coding.

Pick Grok 4.20 Multi-Agent for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a larger context window (2M against 205K tokens).

No benchmark has tested both yet. GLM 5.1 has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); Grok 4.20 Multi-Agent has none yet. Compare them on price and context instead.

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, Grok 4.20 Multi-Agent not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GLM 5.1 $4.40 against Grok 4.20 Multi-Agent $2.50 per million output tokens, 1.8x apart.
Context window
GLM 5.1 takes 205K tokens, Grok 4.20 Multi-Agent 2M.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index16 boards measured
Coding benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
LMArena WebDev1508Not measuredOnly GLM 5.1 measured
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: coding1485Not measuredOnly GLM 5.1 measured
LMArena Text: software and IT1484Not measuredOnly GLM 5.1 measured
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML1508Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 22 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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 measured
Agentic work benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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 apps1180Not 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 slides1170Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1188Not 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 24 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
Reasoning benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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 prompts1473Not measuredOnly GLM 5.1 measured
LMArena Text: expert1478Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts in English1482Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Math benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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: math1473Not measuredOnly GLM 5.1 measured
LMArena Text: mathematical work1470Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
Knowledge benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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: science1478Not measuredOnly GLM 5.1 measured
LMArena Text: medicine and healthcare1474Not measuredOnly GLM 5.1 measured
LMArena Text: legal and government1465Not measuredOnly GLM 5.1 measured
LMArena Text: business and finance1452Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
Web design benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
Design Arena: websites1290Not measuredOnly GLM 5.1 measured
Design Arena: UI components1292Not measuredOnly GLM 5.1 measured
Design Arena: game dev1265Not measuredOnly GLM 5.1 measured
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 art1142Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards measured
General benchmarks for GLM 5.1 and Grok 4.20 Multi-Agent
BenchmarkGLM 5.1Grok 4.20 Multi-AgentLeader
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 Text1463Not measuredOnly GLM 5.1 measured
LMArena Text: instruction following1453Not measuredOnly GLM 5.1 measured
LMArena Text: creative writing1453Not measuredOnly GLM 5.1 measured
LMArena Text: English1476Not measuredOnly GLM 5.1 measured
LMArena Text: non-English1448Not measuredOnly GLM 5.1 measured
LMArena Text: Chinese1515Not measuredOnly GLM 5.1 measured
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: French1470Not measuredOnly GLM 5.1 measured
LMArena Text: Spanish1468Not measuredOnly GLM 5.1 measured
LMArena Text: Russian1454Not measuredOnly GLM 5.1 measured
LMArena Text: Polish1449Not measuredOnly GLM 5.1 measured
LMArena Text: multi-turn1473Not measuredOnly GLM 5.1 measured
LMArena Text: longer queries1467Not measuredOnly GLM 5.1 measured
LMArena Text: writing and language1454Not measuredOnly GLM 5.1 measured
LMArena Text: entertainment and media1442Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 24 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
Grok 4.20 Multi-Agent$0.0025Fits in one request

Grok 4.20 Multi-Agent costs less

Repository review

50K input + 3K output tokens

GLM 5.1$0.083Fits in one request
Grok 4.20 Multi-Agent$0.070Fits in one request

Grok 4.20 Multi-Agent costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds the context window
Grok 4.20 Multi-Agent$0.275Fits in one request

Grok 4.20 Multi-Agent 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 Grok 4.20 Multi-Agent
SpecificationZ.ai GLM 5.1SpaceXAI Grok 4.20 Multi-Agent
MakerZ.aixAI
WeightsOpen weightsNo public weights listed
ReleasedApril 7, 2026March 31, 2026
Context window205K2M
Input $/Mtok$1.40$1.25
Output $/Mtok$4.40$2.50
Coding index49.2Not benchmarked
Independent measurements behind it30
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Grok 4.20 Multi-Agent for coding?

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Grok 4.20 Multi-Agent has none, so the two cannot be ranked on coding. Pick Grok 4.20 Multi-Agent for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a larger context window (2M against 205K tokens).

Which is cheaper, GLM 5.1 or Grok 4.20 Multi-Agent?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Grok 4.20 Multi-Agent costs $1.25 and $2.50. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or Grok 4.20 Multi-Agent?

Grok 4.20 Multi-Agent, with 2M tokens against 205K.

Has any benchmark tested both GLM 5.1 and Grok 4.20 Multi-Agent?

No benchmark has tested both yet. GLM 5.1 has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); Grok 4.20 Multi-Agent has none yet. Compare them on price and context instead. Data as of October 21, 2026.

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