Model comparison
GLM-4.7 vs Grok 4.20 (Non-Reasoning)
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 42.0 on the Noometry Index. GLM-4.7 costs 1.6× less per token, which makes it the better buy when Grok 4.20 (Non-Reasoning)'s lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
Summary
- They share 30 benchmarks with published results for both. GLM-4.7 scores higher in 1 category and Grok 4.20 (Non-Reasoning) in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 (Non-Reasoning) leads 52.3 to 24.3.
- The biggest single-benchmark swing is Terminal-Bench: 33.4% for GLM-4.7 and 57.3% for Grok 4.20 (Non-Reasoning).
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 (Non-Reasoning).
- Grok 4.20 (Non-Reasoning) accepts more context: 1M tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7 | Grok 4.20 (Non-Reasoning) | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 42.0 | 48.6 |
| Released | 2025-12-22 | 2026-02-17 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 30K |
| Input $ / M tokens | $0.60 | $1.25 |
| Output $ / M tokens | $2.20 | $2.50 |
| Results tracked | 36 | 46 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), Grok 4.20 (Non-Reasoning): 42.1 (#112)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena WebDev | 1435 | 1375 |
| LMArena Coding | 1454 | 1459 |
| ALE-Bench | 399.48 | 1,150 |
| SciCode | 45.1% | — |
| WeirdML | — | 52.3% |
Agentic & Tool Use Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 26.5 (#103), Grok 4.20 (Non-Reasoning): 34.4 (#46)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| Terminal-Bench | 33.4% | 57.3% |
| Vending-Bench 2 | 2,377 | 4,663 |
| τ²-bench Banking | — | 18% |
| LMArena Search | — | 1189 |
Reasoning Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 24.3 (#164), Grok 4.20 (Non-Reasoning): 52.3 (#32)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| Chess Puzzles | 6% | 24% |
| LMArena Hard Prompts | 1443 | 1451 |
| Epoch Capabilities Index | 143.51 | 151.98 |
| ARC-AGI-2 | — | 65.1% |
| SimpleBench | 47.7% | — |
| Kagi LLM Benchmark | — | 75% |
| NYT Connections (extended) | — | 85.4% |
| ARC-AGI-1 | — | 89.5% |
| CritPt | 1.7% | — |
| Thematic Generalization | — | 63.8% |
| DTBench | — | 90.1% |
| LMCA | — | 38.7% |
| ForecastBench | — | 61.4 |
Math Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 38.6 (#135), Grok 4.20 (Non-Reasoning): 48.2 (#65)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 92.2% |
| ProofBench | 6% | 14% |
| LMArena Math | 1423 | 1455 |
| FrontierMath (Tiers 1-3) | — | 44.9% |
| FrontierMath Tier 4 | — | 17.1% |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 47.0 (#80), Grok 4.20 (Non-Reasoning): 52.8 (#60)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| GPQA Diamond | 83.3% | 89.3% |
| SimpleQA Verified | 32.2% | 30.2% |
| LMArena Expert | 1424 | 1439 |
| Vectara Hallucination Rate | 11.7% | — |
Multimodal Not comparable
GLM-4.7: —, Grok 4.20 (Non-Reasoning): 33.3 (#98)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Vision | — | 1263 |
| Blueprint-Bench 2 | — | 0% |
| LMArena Document | — | 1416 |
Multilingual Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 52.8 (#79), Grok 4.20 (Non-Reasoning): 54.5 (#40)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Non-English | 1417 | 1441 |
| LMArena Chinese | 1495 | 1481 |
| LMArena French | 1432 | 1476 |
| LMArena German | 1424 | 1465 |
| LMArena Japanese | 1439 | 1449 |
| LMArena Korean | 1399 | 1417 |
| LMArena Russian | 1423 | 1458 |
| LMArena Spanish | 1434 | 1443 |
Instruction Following Too close to call
GLM-4.7: 74.4 (#95), Grok 4.20 (Non-Reasoning): 74.8 (#83)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Instruction Following | 1411 | 1420 |
Long Context Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 42.8 (#116), Grok 4.20 (Non-Reasoning): 45.5 (#34)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| CL-bench | 15.9% | 22.2% |
| CL-bench Life | 10.9% | 11.9% |
| LMArena Longer Query | 1432 | 1437 |
Writing & Preference Grok 4.20 (Non-Reasoning) leads
GLM-4.7: 60.9 (#93), Grok 4.20 (Non-Reasoning): 65.7 (#44)
| Benchmark | GLM-4.7 | Grok 4.20 (Non-Reasoning) |
|---|---|---|
| LMArena Text | 1435 | 1451 |
| LMArena Creative Writing | 1401 | 1438 |
| EQ-Bench Creative Writing | 1413 | 1574 |
| LMArena Multi-Turn | 1446 | 1456 |
Frequently asked questions
Is GLM-4.7 better than Grok 4.20 (Non-Reasoning)?
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 42.0 on the Noometry Index. GLM-4.7 costs 1.6× less per token, which makes it the better buy when Grok 4.20 (Non-Reasoning)'s lead doesn't matter for your workload.
Which is cheaper, GLM-4.7 or Grok 4.20 (Non-Reasoning)?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Grok 4.20 (Non-Reasoning) lists at $1.25 and $2.50.
Is GLM-4.7 or Grok 4.20 (Non-Reasoning) better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 42.1 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 (Non-Reasoning) does, with 1M tokens against 205K.
How many benchmarks do GLM-4.7 and Grok 4.20 (Non-Reasoning) share?
30 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Grok 4.20 (Non-Reasoning) has 46.