Model comparison
GLM-5 vs Grok-2 (Dec 2024)
GLM-5 is the stronger model overall, scoring 46.1 to 33.7 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. GLM-5 scores higher in 8 categories and Grok-2 (Dec 2024) in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5 leads 46.4 to 20.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 80% for GLM-5 and 11.5% for Grok-2 (Dec 2024).
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | Grok-2 (Dec 2024) | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 46.1 | 33.7 |
| Released | 2026-02-11 | 2024-08-13 |
| Weights | Open | Proprietary |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $3.20 | — |
| Results tracked | 45 | 34 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), Grok-2 (Dec 2024): 33.3 (#258)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| WeirdML | 48.2% | 22.2% |
| LMArena Coding | 1461 | 1287 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| LiveBench Coding | — | 46.4% |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), Grok-2 (Dec 2024): —
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning GLM-5 leads
GLM-5: 27.6 (#116), Grok-2 (Dec 2024): 16.9 (#299)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| SimpleBench | 53.2% | 22.7% |
| LMArena Hard Prompts | 1452 | 1272 |
| Epoch Capabilities Index | 145.83 | 130.48 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| LiveBench Reasoning | — | 54.8% |
| DTBench | — | 65.2% |
| LiveBench Data Analysis | — | 54.5% |
| ForecastBench | 61 | — |
| LiveBench | — | 54.3% |
Math GLM-5 leads
GLM-5: 46.4 (#71), Grok-2 (Dec 2024): 20.8 (#284)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 11.5% |
| LMArena Math | 1440 | 1283 |
| FrontierMath (Feb 2025 set) | 16.4% | 0.7% |
| MathArena Final-Answer Competitions | 65.7% | — |
| LiveBench Math | — | 54.9% |
| MATH Level 5 | — | 63.5% |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), Grok-2 (Dec 2024): 29.8 (#233)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| GPQA Diamond | 87.8% | 53.8% |
| LMArena Expert | 1454 | 1254 |
| Confabulations | — | 20.1% |
| Vectara Hallucination Rate | 10.1% | — |
Multilingual GLM-5 leads
GLM-5: 53.7 (#58), Grok-2 (Dec 2024): 43.1 (#188)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Non-English | 1430 | 1282 |
| LMArena Chinese | 1511 | 1289 |
| LMArena French | 1455 | 1318 |
| LMArena German | 1445 | 1287 |
| LMArena Japanese | 1416 | 1244 |
| LMArena Korean | 1423 | 1237 |
| LMArena Russian | 1436 | 1286 |
| LMArena Spanish | 1454 | 1281 |
Instruction Following GLM-5 leads
GLM-5: 75.2 (#67), Grok-2 (Dec 2024): 66.9 (#202)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Instruction Following | 1428 | 1270 |
| LiveBench Instruction Following | — | 69.6% |
Long Context GLM-5 leads
GLM-5: 44.7 (#60), Grok-2 (Dec 2024): 38.8 (#190)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Longer Query | 1446 | 1276 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), Grok-2 (Dec 2024): 48.6 (#198)
| Benchmark | GLM-5 | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Text | 1446 | 1305 |
| LMArena Creative Writing | 1439 | 1284 |
| LMArena Multi-Turn | 1456 | 1290 |
| Short-Story Creative Writing | — | 63.6% |
| EQ-Bench Creative Writing | 1601 | — |
| LiveBench Language | — | 45.6% |
Frequently asked questions
Is GLM-5 better than Grok-2 (Dec 2024)?
GLM-5 is the stronger model overall, scoring 46.1 to 33.7 on the Noometry Index.
Is GLM-5 or Grok-2 (Dec 2024) better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 33.3 in the Noometry coding category.
How many benchmarks do GLM-5 and Grok-2 (Dec 2024) share?
23 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Grok-2 (Dec 2024) has 34.