Model comparison
GLM-5 vs Grok 4.3
Head-to-head evidence from 17 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #26 (Supported); Grok 4.3 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and Grok 4.3 share 17 comparable benchmark results. 3 of 8 categories are comparable. 33 results are unique to GLM-5; 9 to Grok 4.3.
Updated July 17, 2026- Shared results
- 17
- GLM-5 only
- 33
- Grok 4.3 only
- 9
- Comparable categories
- 3 / 8
Pick GLM-5 if you want the stronger benchmark profile. Grok 4.3 only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5 has the cleaner BenchAlign overall profile here, landing at 65.98 versus 65.07. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-5's sharpest advantage is in knowledge, where it averages 66.6 against 42.4. The single biggest benchmark swing on the page is HLE, 50.4% to 35%.
GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $1.25 input / $2.50 output per 1M tokens for Grok 4.3. Grok 4.3 is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Grok 4.3 gives you the larger context window at 1M, compared with 200K for GLM-5.
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 | Δ | Grok 4.3 |
|---|---|---|---|
| Knowledge | GLM-566.6 | Margin← 24.2 | Grok 4.342.4 |
| Coding | GLM-566.3 | Margin← 19.0 | Grok 4.347.3 |
| Inst. Following | GLM-592.6 | Margin← 11.3 | Grok 4.381.3 |
| Agentic | GLM-556.2 | MarginNo overlap | Grok 4.3Not measured |
| Reasoning | GLM-560.8 | MarginNo overlap | Grok 4.3Not measured |
| Math | GLM-556.3 | MarginNo overlap | Grok 4.3Not measured |
| Multilingual | GLM-583.1 | MarginNo overlap | Grok 4.3Not measured |
| Multimodal | GLM-5Not measured | MarginNo overlap | Grok 4.378.1 |
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 | Grok 4.3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | Grok 4.3$1.25 input / $2.5 output | Grok 4.3 has the lower combined listed price. |
| Generation speedtokens per second | GLM-574 tok/s | Grok 4.3209 tok/s | Grok 4.3 has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-51.64 s | Grok 4.312.36 s | GLM-5 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-5200K | Grok 4.31M | Grok 4.3 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | GLM-5 | Grok 4.3 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | — | Not comparable |
| Claw-EvalSource | 57.7% | — | Not comparable |
| QwenClawBenchSource | 54.1% | — | Not comparable |
| τ³-bench resultsSource | 65.6% | — | Not comparable |
| DeepPlanningSource | 14.6% | — | Not comparable |
| ToolathlonSource | 38% | — | Not comparable |
| MCP AtlasSource | 31.1% | — | Not comparable |
| MCP-TasksSource | 60.8% | — | Not comparable |
| WideResearchSource | 69.8% | — | Not comparable |
| τ²-bench resultsSource | 98.2% | 97.7% | GLM-5 leads |
| CyberGymSource | 43.2% | — | Not comparable |
| APEX-Agents-AASource | 14.5% | 17.0% | Grok 4.3 leads |
| Gert LabsSource | 50.99% | 43.86% | GLM-5 leads |
| GDPval-AASource | — | 29.2% | Not comparable |
| AA Agentic IndexSource | — | 24.1% | Not comparable |
| GDPval-AASource | — | 1085 | Not comparable |
| ResearchClawBenchSource | — | 12.4% | Not comparable |
CodingGLM-5 wins10 benchmarks
| Benchmark | GLM-5 | Grok 4.3 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.8% | — | Not comparable |
| SWE-bench Verified*Source | 72.8% | — | Not comparable |
| SWE-bench ProSource | 55.1% | — | Not comparable |
| SWE MultilingualSource | 73.3% | — | Not comparable |
| SWE-RebenchSource | 62.8% | — | Not comparable |
| React Native EvalsSource | 74.8% | — | Not comparable |
| Terminal-Bench HardSource | 43.2% | 37.9% | GLM-5 leads |
| AA-SciCodeSource | 46.2% | 47.3% | Grok 4.3 leads |
| SciCodeSource | — | 47.3% | Not comparable |
| AA Coding IndexSource | — | 42.3% | Not comparable |
Reasoning4 benchmarks
KnowledgeGLM-5 wins12 benchmarks
| Benchmark | GLM-5 | Grok 4.3 | Result |
|---|---|---|---|
| GPQASource | 86% | 90.1% | Grok 4.3 leads |
| GPQA-DSource | 86.0% | — | Not comparable |
| SuperGPQASource | 66.8% | — | Not comparable |
| MMLU-ProSource | 85.7% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 85.8% | — | Not comparable |
| HLESource | 50.4% | 35% | GLM-5 leads |
| Artificial Analysis Intelligence IndexSource | 39.5% | 37.6% | GLM-5 leads |
| AA-GPQA DiamondSource | 82.0% | 90.1% | Grok 4.3 leads |
| AA-HLESource | 27.2% | 35.0% | Grok 4.3 leads |
| AA-Omniscience IndexSource | 2.0% | 18.3% | Grok 4.3 leads |
| AA-Omniscience AccuracySource | 26.9% | 34.6% | Grok 4.3 leads |
| AA-Omniscience Hallucination RateSource | 34.0% | 25.0% | Grok 4.3 leads |
Math8 benchmarks
| Benchmark | GLM-5 | Grok 4.3 | Result |
|---|---|---|---|
| AIME26Source | 95.8% | — | Not comparable |
| AIME25 (Arcee)Source | 93.3% | — | Not comparable |
| HMMT Feb 2025Source | 97.5% | — | Not comparable |
| HMMT Nov 2025Source | 96.9% | — | Not comparable |
| HMMT Feb 2026Source | 86.4% | — | Not comparable |
| MMAnswerBenchSource | 82.5% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 16.434% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.100% | — | Not comparable |
Multilingual2 benchmarks
Multimodal3 benchmarks
Frequently Asked Questions (4)
Which is better, GLM-5 or Grok 4.3?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 65.98 to 65.07. The biggest single separator in this matchup is HLE, where the scores are 50.4% and 35%.
Which is better for knowledge tasks, GLM-5 or Grok 4.3?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.6 versus 42.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5 or Grok 4.3?
GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 47.3. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Which is better for instruction following, GLM-5 or Grok 4.3?
GLM-5 has the edge for instruction following in this comparison, averaging 92.6 versus 81.3. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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