Model comparison
GLM-5 vs Grok 4.20 Multi-Agent
GLM-5 and Grok 4.20 Multi-Agent score almost the same on the Noometry Index (46.1 vs 46.2), so choose on price, context window or the category you care about most.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-5 scores higher in 6 categories and Grok 4.20 Multi-Agent in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 27.6.
- The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 89.6% for Grok 4.20 Multi-Agent.
- Both cost about the same: $1 input and $3.20 output per million tokens.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 46.1 | 46.2 |
| Released | 2026-02-11 | 2026-03-09 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 30K |
| Input $ / M tokens | $1 | $1.25 |
| Output $ / M tokens | $3.20 | $2.50 |
| Results tracked | 45 | 20 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), Grok 4.20 Multi-Agent: 43.0 (#92)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1461 | 1457 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), Grok 4.20 Multi-Agent: —
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| LMArena Search | — | 1204 |
| Vending-Bench 2 | 4,432 | — |
Reasoning Grok 4.20 Multi-Agent leads
GLM-5: 27.6 (#116), Grok 4.20 Multi-Agent: 43.9 (#48)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| NYT Connections (extended) | 74.8% | 89.6% |
| LMArena Hard Prompts | 1452 | 1448 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| Epoch Capabilities Index | 145.83 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 46.4 (#71), Grok 4.20 Multi-Agent: 39.4 (#104)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1440 | 1442 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), Grok 4.20 Multi-Agent: 40.4 (#119)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1454 | 1445 |
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
Multimodal Not comparable
GLM-5: —, Grok 4.20 Multi-Agent: 40.5 (#48)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | — | 1259 |
Multilingual Too close to call
GLM-5: 53.7 (#58), Grok 4.20 Multi-Agent: 54.4 (#43)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1430 | 1440 |
| LMArena Chinese | 1511 | 1475 |
| LMArena French | 1455 | 1466 |
| LMArena German | 1445 | 1456 |
| LMArena Japanese | 1416 | 1405 |
| LMArena Korean | 1423 | 1416 |
| LMArena Russian | 1436 | 1457 |
| LMArena Spanish | 1454 | 1447 |
Instruction Following Too close to call
GLM-5: 75.2 (#67), Grok 4.20 Multi-Agent: 74.8 (#84)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1428 | 1420 |
Long Context Too close to call
GLM-5: 44.7 (#60), Grok 4.20 Multi-Agent: 43.7 (#88)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1446 | 1431 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), Grok 4.20 Multi-Agent: 64.0 (#59)
| Benchmark | GLM-5 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1446 | 1450 |
| LMArena Creative Writing | 1439 | 1436 |
| LMArena Multi-Turn | 1456 | 1452 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than Grok 4.20 Multi-Agent?
GLM-5 and Grok 4.20 Multi-Agent score almost the same on the Noometry Index (46.1 vs 46.2), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5 or Grok 4.20 Multi-Agent?
GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is GLM-5 or Grok 4.20 Multi-Agent better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 43.0 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 205K.
How many benchmarks do GLM-5 and Grok 4.20 Multi-Agent share?
18 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Grok 4.20 Multi-Agent has 20.