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Z.AI: GLM 4.5
Z.AI: GLM 4.5

GLM 4.5 is the latest flagship foundation model, purpose-built for agent-driven applications. Built on a Mixture-of-Experts (MoE) architecture, it supports context lengths of up to 128K tokens and offers major improvements in reasoning, code generation, and agent alignment. The model features a hybrid inference system with two modes: a “thinking mode” for complex reasoning and tool use, and a “non-thinking mode” for fast, real-time responses. Reasoning behavior can be easily managed with a simple boolean toggle.
| Creator | zAI |
| Release Date | July, 2025 |
| License | MIT |
| Context Window | 131,072 |
| Image Input Support | No |
| Open Source (Weights) | Yes |
| Parameters | 355B, 32B active at inference time |
| Model Weights | Click here |
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MiniMax: MiniMax 01
MiniMax: MiniMax 01

MiniMax-01 integrates MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding, combining multimodal strengths in a single model. It features 456B parameters, with 45.9B active per inference, and supports context lengths of up to 4 million tokens.
The text component uses a hybrid architecture that blends Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE). The vision component follows a “ViT-MLP-LLM” framework, trained on top of the text model to enable advanced multimodal reasoning.
| Creator | MiniMax |
| Release Date | January, 2025 |
| License | MiniMax Model License Agreement |
| Context Window | 1,000,192 |
| Image Input Support | No |
| Open Source (Weights) | Yes |
| Parameters | 456B, 45.9B active at inference time |
| Model Weights | Click here |
Performance Benchmarks
Core Academic Benchmarks
| Tasks | GPT-4o (11-20) | Claude-3.5-Sonnet (10-22) | Gemini-1.5-Pro (002) | Gemini-2.0-Flash (exp) | Qwen2.5-72B-Inst. | DeepSeek-V3 | Llama-3.1-405B-Inst. | MiniMax-Text-01 |
|---|---|---|---|---|---|---|---|---|
| General | ||||||||
| MMLU* | 85.7 | 88.3 | 86.8 | 86.5 | 86.1 | 88.5 | 88.6 | 88.5 |
| MMLU-Pro* | 74.4 | 78.0 | 75.8 | 76.4 | 71.1 | 75.9 | 73.3 | 75.7 |
| SimpleQA | 39.0 | 28.1 | 23.4 | 26.6 | 10.3 | 24.9 | 23.2 | 23.7 |
| C-SimpleQA | 64.6 | 56.8 | 59.4 | 63.3 | 52.2 | 64.8 | 54.7 | 67.4 |
| IFEval (avg) | 84.1 | 90.1 | 89.4 | 88.4 | 87.2 | 87.3 | 86.4 | 89.1 |
| Arena-Hard | 92.4 | 87.6 | 85.3 | 72.7 | 81.2 | 91.4 | 63.5 | 89.1 |
| Reasoning | ||||||||
| GPQA* (diamond) | 46.0 | 65.0 | 59.1 | 62.1 | 49.0 | 59.1 | 50.7 | 54.4 |
| DROP* (F1) | 89.2 | 88.8 | 89.2 | 89.3 | 85.0 | 91.0 | 92.5 | 87.8 |
| Mathematics | ||||||||
| GSM8k* | 95.6 | 96.9 | 95.2 | 95.4 | 95.8 | 96.7 | 96.7 | 94.8 |
| MATH* | 76.6 | 74.1 | 84.6 | 83.9 | 81.8 | 84.6 | 73.8 | 77.4 |
| Coding | ||||||||
| MBPP + | 76.2 | 75.1 | 75.4 | 75.9 | 77.0 | 78.8 | 73.0 | 71.7 |
| HumanEval | 90.2 | 93.7 | 86.6 | 89.6 | 86.6 | 92.1 | 89.0 | 86.9 |
Ruler
| Model | 4k | 8k | 16k | 32k | 64k | 128k | 256k | 512k | 1M |
|---|---|---|---|---|---|---|---|---|---|
| GPT-4o (11-20) | 0.970 | 0.921 | 0.890 | 0.888 | 0.884 | – | – | – | – |
| Claude-3.5-Sonnet (10-22) | 0.965 | 0.960 | 0.957 | 0.950 | 0.952 | 0.938 | – | – | – |
| Gemini-1.5-Pro (002) | 0.962 | 0.960 | 0.960 | 0.958 | 0.938 | 0.917 | 0.916 | 0.861 | 0.850 |
| Gemini-2.0-Flash (exp) | 0.960 | 0.960 | 0.951 | 0.957 | 0.937 | 0.860 | 0.797 | 0.709 | – |
| MiniMax-Text-01 | 0.963 | 0.961 | 0.953 | 0.954 | 0.943 | 0.947 | 0.945 | 0.928 | 0.910 |
LongBench V2
| Model | overall | easy | hard | short | medium | long |
|---|---|---|---|---|---|---|
| Human | 53.7 | 100.0 | 25.1 | 47.2 | 59.1 | 53.7 |
| w/ CoT | ||||||
| GPT-4o (11-20) | 51.4 | 54.2 | 49.7 | 59.6 | 48.6 | 43.5 |
| Claude-3.5-Sonnet (10-22) | 46.7 | 55.2 | 41.5 | 53.9 | 41.9 | 44.4 |
| Deepseek-V3 | – | – | – | – | – | – |
| Qwen2.5-72B-Inst. | 43.5 | 47.9 | 40.8 | 48.9 | 40.9 | 39.8 |
| MiniMax-Text-01 | 56.5 | 66.1 | 50.5 | 61.7 | 56.7 | 47.2 |
| w/o CoT | ||||||
| GPT-4o (11-20) | 50.1 | 57.4 | 45.6 | 53.3 | 52.4 | 40.2 |
| Claude-3.5-Sonnet (10-22) | 41.0 | 46.9 | 37.3 | 46.1 | 38.6 | 37.0 |
| Deepseek-V3 | 48.7 | – | – | – | – | – |
| Qwen2.5-72B-Inst. | 42.1 | 42.7 | 41.8 | 45.6 | 38.1 | 44.4 |
| MiniMax-Text-01 | 52.9 | 60.9 | 47.9 | 58.9 | 52.6 | 43.5 |
MTOB
| Context Type | no context | half book | full book | Δ half book | Δ full book |
|---|---|---|---|---|---|
| eng → kalam (ChrF) | |||||
| GPT-4o (11-20) | 9.90 | 54.30 | – | 44.40 | – |
| Claude-3.5-Sonnet (10-22) | 20.22 | 53.62 | 55.65 | 33.39 | 35.42 |
| Gemini-1.5-Pro (002) | 16.79 | 53.68 | 57.90 | 36.89 | 41.11 |
| Gemini-2.0-Flash (exp) | 12.20 | 49.50 | 53.30 | 37.30 | 41.10 |
| Qwen-Long | 16.55 | 48.48 | 45.94 | 31.92 | 29.39 |
| MiniMax-Text-01 | 6.0 | 51.74 | 51.60 | 45.7 | 45.6 |
| kalam → eng (BLEURT) | |||||
| GPT-4o (11-20) | 33.20 | 58.30 | – | 25.10 | – |
| Claude-3.5-Sonnet (10-22) | 31.42 | 59.70 | 62.30 | 28.28 | 30.88 |
| Gemini-1.5-Pro (002) | 32.02 | 61.52 | 63.09 | 29.50 | 31.07 |
| Gemini-2.0-Flash (exp) | 33.80 | 57.50 | 57.00 | 23.70 | 23.20 |
| Qwen-Long | 30.13 | 53.14 | 32.15 | 23.01 | 2.02 |
| MiniMax-Text-01 | 33.65 | 57.10 | 58.00 | 23.45 | 24.35 |
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DeepSeek: DeepSeek R1 0528
DeepSeek: DeepSeek R1 0528

Update (May 28): The original DeepSeek R1 now delivers performance comparable to OpenAI’s o1, but is fully open-source with transparent reasoning tokens. The model has 671B parameters, with 37B active per inference pass—making it one of the largest openly available models.
| Creator | Deepseek |
| Release Date | May, 2025 |
| License | MIT |
| Context Window | 128,000 |
| Image Input Support | No |
| Open Source (Weights) | Yes |
| Parameters | 685B, 37B active at inference time |
| Model Weights | Click here |
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Yes, you can adjust your plan at any time to better suit your needs. Upgrades will take effect immediately, while downgrades will be applied at the start of your next billing cycle.
Yes, you can adjust your plan at any time to better suit your needs. Upgrades will take effect immediately, while downgrades will be applied at the start of your next billing cycle.
Yes, you can adjust your plan at any time to better suit your needs. Upgrades will take effect immediately, while downgrades will be applied at the start of your next billing cycle.
Yes, you can adjust your plan at any time to better suit your needs. Upgrades will take effect immediately, while downgrades will be applied at the start of your next billing cycle.
Yes, you can adjust your plan at any time to better suit your needs. Upgrades will take effect immediately, while downgrades will be applied at the start of your next billing cycle.




















