Model comparison
GLM-5.2 vs Grok 4.3
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.2 #37 (Estimated); Grok 4.3 #31 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.2 and Grok 4.3 share 20 comparable benchmark results. 2 of 8 categories are comparable. 23 results are unique to GLM-5.2; 5 to Grok 4.3.
Updated July 23, 2026- Shared results
- 20
- GLM-5.2 only
- 23
- Grok 4.3 only
- 5
- Comparable categories
- 2 / 8
Pick Grok 4.3 if you want the stronger benchmark profile. GLM-5.2 only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Grok 4.3 has the cleaner BenchAlign overall profile here, landing at 65.1 versus 63.96. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-5.2 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $1.25 input / $2.50 output per 1M tokens for Grok 4.3.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-5.2 | Δ | Grok 4.3 |
|---|---|---|---|
| Knowledge | GLM-5.259.6 | Margin← 17.2 | Grok 4.342.4 |
| Coding | GLM-5.262.1 | Margin← 14.8 | Grok 4.347.3 |
| Agentic | GLM-5.281.0 | MarginNo overlap | Grok 4.3Not measured |
| Math | GLM-5.295.9 | MarginNo overlap | Grok 4.3Not measured |
| Multimodal | GLM-5.2Not measured | MarginNo overlap | Grok 4.378.1 |
| Inst. Following | GLM-5.2Not measured | MarginNo overlap | Grok 4.381.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5.2 | Grok 4.3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.2$1.4 input / $4.4 output | Grok 4.3$1.25 input / $2.5 output | Grok 4.3 has the lower combined listed price. |
| Generation speedtokens per second | GLM-5.2Not available | Grok 4.3209 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.2Not available | Grok 4.312.36 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.21M | Grok 4.31M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | GLM-5.2 | Grok 4.3 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 81% | — | Not comparable |
| MCP AtlasSource | 76.8% | — | Not comparable |
| ToolathlonSource | 48.2% | — | Not comparable |
| AA Agentic IndexSource | 43.1% | 24.1% | GLM-5.2 leads |
| τ²-bench resultsSource | 99.1% | 97.7% | GLM-5.2 leads |
| GDPval-AASource | 50.7% | 29.2% | GLM-5.2 leads |
| GDPval-AASource | 1514 | 1085 | GLM-5.2 leads |
| APEX-Agents-AASource | 33.7% | 17.0% | GLM-5.2 leads |
| ResearchClawBenchSource | 20.7% | 12.4% | GLM-5.2 leads |
| AA BriefcaseSource | 1260 | — | Not comparable |
| AA AutomationBenchSource | 27.8% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.7% | — | Not comparable |
| AA Harvey LABSource | 91.0% | — | Not comparable |
| AA ITBenchSource | 42.7% | — | Not comparable |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 50.8% | — | Not comparable |
| aaTerminalBench21Source | 77.9% | — | Not comparable |
| Gert LabsSource | — | 43.86% | Not comparable |
CodingGLM-5.2 wins8 benchmarks
| Benchmark | GLM-5.2 | Grok 4.3 | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.1% | — | Not comparable |
| NL2RepoSource | 48.9% | — | Not comparable |
| Terminal-Bench 2.0Source | 81.0% | — | Not comparable |
| ProgramBenchSource | 63.7% | — | Not comparable |
| cursorBench32Source | 55.0% | — | Not comparable |
| AA Coding IndexSource | 68.8% | 42.3% | GLM-5.2 leads |
| AA-SciCodeSource | 50.5% | 47.3% | GLM-5.2 leads |
| SciCodeSource | — | 47.3% | Not comparable |
Reasoning2 benchmarks
KnowledgeGLM-5.2 wins11 benchmarks
| Benchmark | GLM-5.2 | Grok 4.3 | Result |
|---|---|---|---|
| GPQASource | 91.2% | 90.1% | GLM-5.2 leads |
| GPQA-DSource | 91.2% | — | Not comparable |
| HLESource | 54.7% | 35% | GLM-5.2 leads |
| HLE w/o toolsSource | 40.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.1% | 37.6% | GLM-5.2 leads |
| AA-GPQA DiamondSource | 89.5% | 90.1% | Grok 4.3 leads |
| AA-HLESource | 40.1% | 35.0% | GLM-5.2 leads |
| AA-Omniscience IndexSource | 4.0% | 18.3% | Grok 4.3 leads |
| AA-Omniscience AccuracySource | 25.1% | 34.6% | Grok 4.3 leads |
| AA-Omniscience Hallucination RateSource | 28.1% | 25.0% | Grok 4.3 leads |
| AA Openness IndexSource | 44.4% | — | Not comparable |
Math4 benchmarks
Multimodal3 benchmarks
Frequently Asked Questions (3)
Which is better, GLM-5.2 or Grok 4.3?
Grok 4.3 is ahead on BenchLM's BenchAlign leaderboard, 65.1 to 63.96. The biggest single separator in this matchup is HLE, where the scores are 54.7% and 35%.
Which is better for knowledge tasks, GLM-5.2 or Grok 4.3?
GLM-5.2 has the edge for knowledge tasks in this comparison, averaging 59.6 versus 42.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5.2 or Grok 4.3?
GLM-5.2 has the edge for coding in this comparison, averaging 62.1 versus 47.3. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
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