Model comparison
GLM-5.1 vs Grok 4.5
Grok 4.5 is the stronger model overall, scoring 55.0 to 47.6 on the Noometry Index.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. GLM-5.1 scores higher in 4 categories and Grok 4.5 in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Grok 4.5 leads 44.4 to 24.8.
- The biggest single-benchmark swing is GBAEval: 0% for GLM-5.1 and 65.4% for Grok 4.5.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.1 | Grok 4.5 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 47.6 | 55.0 |
| Released | 2026-04-07 | 2026-07-08 |
| Weights | Open | Proprietary |
| Context window | 200K | 500K |
| Max output | 131K | 500K |
| Input $ / M tokens | $1.40 | $2 |
| Output $ / M tokens | $4.40 | $6 |
| Results tracked | 41 | 52 |
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Category by category
Coding Grok 4.5 leads
GLM-5.1: 48.5 (#52), Grok 4.5: 51.7 (#34)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena WebDev | 1509 | 1552 |
| SciCode | 43.8% | 54.1% |
| WeirdML | 57.1% | 46.4% |
| LMArena Coding | 1486 | 1473 |
| ALE-Bench | 887.1 | 1,309 |
| SWE-bench Verified | 74.2% | — |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
Agentic & Tool Use Grok 4.5 leads
GLM-5.1: 24.8 (#106), Grok 4.5: 44.4 (#15)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| APEX-Agents | 40.9% | 56.2% |
| GBAEval | 0% | 65.4% |
| Vending-Bench 2 | 5,634 | 3,887 |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| ExploitBench | 18.1% | — |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
Reasoning Grok 4.5 leads
GLM-5.1: 38.2 (#57), Grok 4.5: 56.0 (#23)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| SimpleBench | 55.1% | 70% |
| NYT Connections (extended) | 77.7% | 79.9% |
| CritPt | 4.6% | 15.4% |
| Chess Puzzles | 19% | 36% |
| LMArena Hard Prompts | 1472 | 1462 |
| Epoch Capabilities Index | 149.86 | 154.02 |
| ARC-AGI-2 | — | 52.6% |
| Kagi LLM Benchmark | — | 83.5% |
| ARC-AGI-1 | — | 87.2% |
| Thematic Generalization | 69.8% | — |
| DTBench | — | 96.5% |
| LMCA | — | 45.2% |
| Surface Evolver Bench | — | 74.4% |
Math Grok 4.5 leads
GLM-5.1: 49.0 (#48), Grok 4.5: 60.7 (#29)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 36.8% | 57.2% |
| OTIS Mock AIME 2024-2025 | 93.3% | 97.8% |
| ProofBench | 22.2% | 31% |
| LMArena Math | 1472 | 1457 |
| FrontierMath Tier 4 | — | 24.4% |
| MathArena Final-Answer Competitions | 67.1% | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge Grok 4.5 leads
GLM-5.1: 55.0 (#45), Grok 4.5: 62.3 (#21)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| GPQA Diamond | 89.9% | 93.4% |
| SimpleQA Verified | 34% | 48.3% |
| LMArena Expert | 1477 | 1466 |
Multimodal Not comparable
GLM-5.1: —, Grok 4.5: 37.8 (#63)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1287 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |
Multilingual Too close to call
GLM-5.1: 55.2 (#34), Grok 4.5: 54.5 (#43)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena Non-English | 1448 | 1439 |
| LMArena Chinese | 1516 | 1497 |
| LMArena French | 1478 | 1458 |
| LMArena German | 1466 | 1448 |
| LMArena Japanese | 1436 | 1425 |
| LMArena Korean | 1423 | 1402 |
| LMArena Russian | 1453 | 1447 |
| LMArena Spanish | 1467 | 1452 |
Instruction Following Too close to call
GLM-5.1: 76.5 (#41), Grok 4.5: 76.3 (#45)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1446 |
Long Context Too close to call
GLM-5.1: 44.9 (#51), Grok 4.5: 44.8 (#54)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | 1467 | 1463 |
Writing & Preference GLM-5.1 leads
GLM-5.1: 67.2 (#29), Grok 4.5: 65.9 (#40)
| Benchmark | GLM-5.1 | Grok 4.5 |
|---|---|---|
| LMArena Text | 1462 | 1448 |
| LMArena Creative Writing | 1454 | 1442 |
| EQ-Bench Creative Writing | 1592 | 1579 |
| LMArena Multi-Turn | 1473 | 1457 |
Frequently asked questions
Is GLM-5.1 better than Grok 4.5?
Grok 4.5 is the stronger model overall, scoring 55.0 to 47.6 on the Noometry Index.
Which is cheaper, GLM-5.1 or Grok 4.5?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Grok 4.5 lists at $2 and $6.
Is GLM-5.1 or Grok 4.5 better for coding?
Grok 4.5 scores higher on coding benchmarks: 51.7 versus 48.5 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 200K.
How many benchmarks do GLM-5.1 and Grok 4.5 share?
35 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Grok 4.5 has 52.