Model comparison
GLM-4.5 vs Grok 4.6
Grok 4.6 is the stronger model overall, scoring 56.9 to 42.0 on the Noometry Index. GLM-4.5 costs 3.0× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 0 categories and Grok 4.6 in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.6 leads 61.4 to 28.6.
- The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 67.3% for Grok 4.6.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Grok 4.6 accepts more context: 500K tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | Grok 4.6 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 42.0 | 56.9 |
| Released | 2025-07-27 | 2026-08-12 |
| Weights | Open | Proprietary |
| Context window | 131K | 500K |
| Max output | 98K | 500K |
| Input $ / M tokens | $0.60 | $2 |
| Output $ / M tokens | $2.20 | $6 |
| Results tracked | 27 | 49 |
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Category by category
Coding Grok 4.6 leads
GLM-4.5: 41.4 (#125), Grok 4.6: 58.5 (#16)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| WeirdML | 40.6% | 67.3% |
| LMArena Coding | 1434 | 1465 |
| ALE-Bench | 344.82 | 1,508 |
| DeepSWE | — | 67.5% |
| FrontierCode | — | 48% |
| SWE-bench Verified (bash only) | 54.2% | — |
| CursorBench | — | 41.4% |
| LMArena WebDev | — | 1617 |
| FrontierSWE | — | 25.3% |
| SciCode | — | 56.5% |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, Grok 4.6: 39.4 (#27)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| APEX-Agents | — | 65.3% |
| GDP.pdf | — | 17.2% |
| Vending-Bench 2 | — | 9,047 |
Reasoning Grok 4.6 leads
GLM-4.5: 28.6 (#100), Grok 4.6: 61.4 (#20)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1447 |
| ARC-AGI-2 | — | 67.1% |
| SimpleBench | — | 75.9% |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | — | 80% |
| ARC-AGI-1 | — | 87.5% |
| CritPt | — | 19.7% |
| Chess Puzzles | — | 40% |
| EBR-Bench | — | 30.5% |
| Mystery Game Puzzles | — | 34% |
| DTBench | — | 97.3% |
| LMCA | — | 48.5% |
| Epoch Capabilities Index | — | 156.44 |
Math Grok 4.6 leads
GLM-4.5: 39.0 (#116), Grok 4.6: 67.0 (#24)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Math | 1427 | 1423 |
| FrontierMath (Tiers 1-3) | — | 66% |
| FrontierMath Tier 4 | — | 31.7% |
| OTIS Mock AIME 2024-2025 | — | 99.2% |
| ProofBench | — | 51% |
Knowledge Grok 4.6 leads
GLM-4.5: 35.9 (#179), Grok 4.6: 63.3 (#20)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Expert | 1433 | 1467 |
| GPQA Diamond | — | 94% |
| Humanity's Last Exam | 8.3% | — |
| SimpleQA Verified | — | 49.3% |
| Confabulations | 11.3% | — |
Multimodal Not comparable
GLM-4.5: —, Grok 4.6: 43.6 (#23)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Vision | — | 1263 |
| Blueprint-Bench 2 | — | 33.2% |
| Furniture Assembly | — | 40% |
| LMArena Document | — | 1452 |
Multilingual Too close to call
GLM-4.5: 52.8 (#77), Grok 4.6: 53.0 (#74)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Non-English | 1417 | 1420 |
| LMArena Chinese | 1465 | 1480 |
| LMArena French | 1418 | 1461 |
| LMArena German | 1407 | 1431 |
| LMArena Japanese | 1415 | 1376 |
| LMArena Korean | 1380 | 1397 |
| LMArena Russian | 1414 | 1422 |
| LMArena Spanish | 1454 | 1404 |
Instruction Following Grok 4.6 leads
GLM-4.5: 74.1 (#104), Grok 4.6: 75.4 (#63)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1431 |
Long Context Grok 4.6 leads
GLM-4.5: 38.2 (#201), Grok 4.6: 44.5 (#66)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Longer Query | 1412 | 1454 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference Grok 4.6 leads
GLM-4.5: 57.5 (#127), Grok 4.6: 62.3 (#80)
| Benchmark | GLM-4.5 | Grok 4.6 |
|---|---|---|
| LMArena Text | 1430 | 1428 |
| LMArena Creative Writing | 1395 | 1428 |
| LMArena Multi-Turn | 1415 | 1425 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Grok 4.6?
Grok 4.6 is the stronger model overall, scoring 56.9 to 42.0 on the Noometry Index. GLM-4.5 costs 3.0× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5 or Grok 4.6?
GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Grok 4.6 lists at $2 and $6.
Is GLM-4.5 or Grok 4.6 better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.5 versus 41.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.6 does, with 500K tokens against 131K.
How many benchmarks do GLM-4.5 and Grok 4.6 share?
19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Grok 4.6 has 49.