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| Attribute |
🤖
Ling-1T
inclusionAI
|
|---|---|
| Company | inclusionAI |
| Release Date | 2025-10-09 |
| Parameters (B) | 1000 |
| Architecture | MoE Transformer |
| Context Window | 128000 |
| Input Modalities | text |
| Open Source | Yes |
| License | mit |
| Score | 0 |
| VRAM (GB) | 2560 |
| Compute | 32× NVIDIA H100 80GB GPUs (or equivalent) with tensor/pipeline parallelism via SGLang or vLLM for full-weight FP8/BF16 inference |
| Benchmark: AIME-2024 | 80.2 |
| Benchmark: AIME-2025 | 70.4 |
| Benchmark: Aider | 83.7 |
| Benchmark: C-Eval | 92.2 |
| Benchmark: GPQA-Diamond | 73.0 |
| Benchmark: HLE | 7.6 |
| Benchmark: IFEval | 86.1 |
| Benchmark: LiveCodeBench | 61.7 |
| Benchmark: MBPP | 96.9 |
| Benchmark: MMLU-Pro | 82.0 |
| Pricing (Input) | — |
| Pricing (Output) | — |