Z ai’s updated GLM 4.6 (Reasoning) is one of the most intelligent open weights models, with near DeepSeek V3.1 (Reasoning) and Qwen3 235B 2507 (Reasoning) level intelligence 🧠 Key intelligence benchmarking takeaways: ➤ Reasoning Model Performance: GLM 4.6 (Reasoning) scores 56 on the Artificial Analysis Intelligence Index, up from GLM 4.5’s score of 51 in reasoning mode ➤ Non-Reasoning Model Performance: In non-reasoning mode, GLM 4.6 achieves a score of 45, placing it 2 points ahead of GPT-5 (minimal, non-reasoning) ➤ Token efficiency: Z ai has increased GLM’s evaluation scores while decreasing output tokens. For GLM 4.6 (Reasoning), we see a material decrease of 14% in token usage to run Artificial Analysis Intelligence Index from 100M to 86M, compared to GLM 4.5 (Reasoning). This is different from other model upgrades we have seen where increase in intelligence is often correlated with increase in output token usage. In non-reasoning mode, GLM 4.6 uses 12M output tokens for the Artificial Analysis Intelligence Index Other model details: ➤🪙 Context Window: 200K token context. This is larger compared to GLM 4.5’s context window of 128K tokens ➤📏 Size: GLM 4.6 has 355B total parameters and 32B active parameters - this is the same as GLM 4.5. For self-deployment, GLM 4.6 will require ~710GB of memory to store the weights in native BF16 precision and cannot be deployed on a single NVIDIA 8xH100 node (~640GB of memory) ➤©️ Licensing: GLM 4.6 is available under the MIT License ➤🌐 Availability: GLM 4.6 is available on Z ai’s first-party API and several third-party APIs such as DeepInfra (FP8), Novita (BF16), GMI Cloud (BF16) and Parasail (FP8)

GLM 4.6 (Reasoning) improves token efficiency, requiring 14M fewer output tokens compared to GLM 4.5 (Reasoning) for the Artificial Analysis Intelligence Index

Full evals independently run by Artificial Analysis

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