Zhipu AI·released 2026-02-11✓ 2 sources
GLM-5 benchmark scores: 12 benchmarks tracked. 50% of its scores are independently reproduced — the rest are self-reported or unverified.
Leads on 0 of 12 benchmarks·best result 83.76 on GPQA diamond (reproduced)·6 of 12 independently reproduced·$1/$3.2 per M tokens
Consensus: LiteLLM · Cross-check: models.dev, OpenRouter · See every model’s pricing →
| Benchmark | Score | Evidence status | Measured |
|---|---|---|---|
| GPQA diamond | 83.76accuracy (%) | reproduced· optimizedT1 | 2026-02-11Epoch AI |
| OTIS Mock AIME 2024-2025 | 79.98accuracy (%) | reproduced· optimizedT1 | 2026-02-11Epoch AI |
| SWE-Bench verified | 72.08accuracy (%) | reproduced· optimizedT1 | 2026-02-11Epoch AI |
| Terminal Bench | 52.42accuracy (%) | unverifiedT1 | 2026-02-11https://www.tbench.ai/leaderboard/terminal-bench/2.0 |
| WeirdML | 48.17accuracy (%) | unverifiedT1 | 2026-02-11WeirdML Leaderboard |
| ARC-AGI | 44.67accuracy (%) | unverified· optimizedT2 | 2026-02-11 |
| SimpleBench | 43.84accuracy (%) | unverifiedT1 | 2026-02-11SimpleBench Leaderboard |
| FrontierMath-2025-02-28-Private | 28.83accuracy (%) | reproduced· optimizedT1 | 2026-02-11Epoch AI |
| CL-bench | 18.7accuracy (%) | unverifiedT2 | 2026-02-11 |
| Chess Puzzles | 5.3accuracy (%) | reproducedT1 | 2026-02-11Epoch AI |
| ARC-AGI-2 | 4.86accuracy (%) | unverifiedT2 | 2026-02-11 |
| FrontierMath-Tier-4-2025-07-01-Private | 3.5accuracy (%) | reproducedT1 | 2026-02-11Epoch AI |
Claims drawn from cited facts, not live model generation.
This model originates from Zhipu AI and was released in 2026, placing it among the more recent entries in that lineage. With 753.91 billion parameters it sits at frontier-scale, and that magnitude is the trade-off itself: far greater capability headroom than compact or mid-size alternatives, at the price of substantially heavier training and inference costs.
4 cited facts
This model is scored on 12 tracked benchmarks. It currently holds no top score on any of them. Its record can be trusted, since the results have been independently reproduced by outside evaluation.
3 cited facts
Its mean gap to the best recorded score across its tracked benchmarks is 36.9 points.
1 cited fact
7 facts cross-checked across data sources: 3 corroborated, 1 single-source, 3 disputed.
Source facts, citations, and refresh stamp for this record.
Sources: epoch_benchmarks, huggingface_models, litellm_prices, modelsdev_models +1 more
GLM-5 is an AI model developed by Zhipu AI, released 2026-02-11. Its benchmark record below tags every score as independently reproduced, self-reported, or unverified.
GLM-5 has recorded scores on 12 benchmarks, each shown with its evidence status.
GLM-5 has recorded scores on 12 benchmarks — GPQA diamond, OTIS Mock AIME 2024-2025, WeirdML, Chess Puzzles, SimpleBench, FrontierMath-2025-02-28-Private, and 6 more. The full table above shows each score with its evidence status.
6 of 12 recorded scores (50%) are independently reproduced rather than self-reported by the lab.
GLM-5 has 12 tracked claims: 6 independently reproduced, 6 unverified.
Listed API pricing: $1 per million input tokens, $3.2 per million output tokens (prices disputed across sources). See the pricing block for the full breakdown.