Model comparison
GLM-5.3-Flash vs Grok 4.20 Multi-Agent
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 45.5 on the Noometry Index.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Grok 4.20 Multi-Agent in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 39.7.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3-Flash | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 49.6 | 45.5 |
| Released | 2026-08-20 | 2026-03-09 |
| Weights | Open | Proprietary |
| Context window | 1M | 1M |
| Max output | 131K | 30K |
| Input $ / M tokens | $0.15 | $1.25 |
| Output $ / M tokens | $0.50 | $2.50 |
| Results tracked | 36 | 20 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.7 (#26), Grok 4.20 Multi-Agent: 42.4 (#91)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1506 | 1458 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| LMArena WebDev | 1614 | — |
| SciCode | 51.6% | — |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use Not comparable
GLM-5.3-Flash: 34.3 (#41), Grok 4.20 Multi-Agent: —
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |
| LMArena Search | — | 1204 |
Reasoning Grok 4.20 Multi-Agent leads
GLM-5.3-Flash: 31.7 (#69), Grok 4.20 Multi-Agent: 42.4 (#44)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Hard Prompts | 1490 | 1448 |
| NYT Connections (extended) | — | 89.6% |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.9 | — |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#38), Grok 4.20 Multi-Agent: 36.6 (#106)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1499 | 1441 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#33), Grok 4.20 Multi-Agent: 39.7 (#116)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1512 | 1445 |
| GPQA Diamond | 90.2% | — |
Multimodal GLM-5.3-Flash leads
GLM-5.3-Flash: 42.6 (#25), Grok 4.20 Multi-Agent: 39.8 (#44)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | 1304 | 1259 |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.2 (#24), Grok 4.20 Multi-Agent: 54.6 (#40)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1462 | 1440 |
| LMArena Chinese | 1529 | 1475 |
| LMArena French | 1495 | 1467 |
| LMArena German | 1457 | 1456 |
| LMArena Japanese | 1420 | 1405 |
| LMArena Korean | 1443 | 1416 |
| LMArena Russian | 1472 | 1457 |
| LMArena Spanish | 1471 | 1447 |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.8 (#17), Grok 4.20 Multi-Agent: 75.0 (#80)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1480 | 1420 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.3 (#41), Grok 4.20 Multi-Agent: 43.7 (#84)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1479 | 1430 |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.4 (#49), Grok 4.20 Multi-Agent: 64.1 (#57)
| Benchmark | GLM-5.3-Flash | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1471 | 1450 |
| LMArena Creative Writing | 1440 | 1435 |
| LMArena Multi-Turn | 1471 | 1451 |
Frequently asked questions
Is GLM-5.3-Flash better than Grok 4.20 Multi-Agent?
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 45.5 on the Noometry Index.
Which is cheaper, GLM-5.3-Flash or Grok 4.20 Multi-Agent?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is GLM-5.3-Flash or Grok 4.20 Multi-Agent better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do GLM-5.3-Flash and Grok 4.20 Multi-Agent share?
18 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Grok 4.20 Multi-Agent has 20.