Model comparison
GLM-5 vs INTELLECT-1
GLM-5 has enough public results to be ranked (#66); INTELLECT-1 does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
Hugging FaceSummary
- They share 1 benchmark with published results for both.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | INTELLECT-1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Hugging Face |
| Noometry Index | 46.1 | — |
| Released | 2026-02-11 | 2024-11-29 |
| Weights | Open | Proprietary |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $3.20 | — |
| Results tracked | 45 | 7 |
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Category by category
Coding Not comparable
GLM-5: 49.0 (#52), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| LMArena Coding | 1461 | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| 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 Not comparable
GLM-5: 27.6 (#116), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| Epoch Capabilities Index | 145.83 | 100.86 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| LMArena Hard Prompts | 1452 | — |
| BIG-Bench Hard | — | 34.9% |
| ForecastBench | 61 | — |
| HellaSwag | — | 71.4% |
| WinoGrande | — | 65.8% |
Math Not comparable
GLM-5: 46.4 (#71), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| LMArena Math | 1440 | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 38.6% |
Knowledge Not comparable
GLM-5: 52.3 (#64), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
| ARC (AI2) Challenge | — | 54.5% |
| MMLU | — | 49.9% |
Multilingual Not comparable
GLM-5: 53.7 (#58), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1423 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-5: 75.2 (#67), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| LMArena Instruction Following | 1428 | — |
Long Context Not comparable
GLM-5: 44.7 (#60), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |
Writing & Preference Not comparable
GLM-5: 66.0 (#38), INTELLECT-1: —
| Benchmark | GLM-5 | INTELLECT-1 |
|---|---|---|
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1439 | — |
| EQ-Bench Creative Writing | 1601 | — |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is GLM-5 better than INTELLECT-1?
GLM-5 has enough public results to be ranked (#66); INTELLECT-1 does not yet, so treat this comparison as directional.
How many benchmarks do GLM-5 and INTELLECT-1 share?
1 benchmark has published results for both models. GLM-5 has 45 scored results on Noometry and INTELLECT-1 has 7.