Highest MMLU Pro score reported. Leads all models on this benchmark.

Matches o4-mini on general knowledge. Runs on single 80GB GPU despite 116.8B params (5.1B active via MoE).

Leads MMLU-Pro leaderboard among available models as of early April 2026.

Broad knowledge and reasoning. 397B total, 17B active params.

Actually scores higher than Seed 2.0 Pro (87.0) on this benchmark.

Strong knowledge reasoning from the 1T MoE open-source model. Thinking mode enabled.

Joint highest MMLU Pro at time of release. Verified by Artificial Analysis.

Strong knowledge breadth. Seed 2.0 Lite variant scores slightly higher at 87.7.

Dense multimodal model, 262k native context.

Only 3.6B active params. Matches o3-mini on general knowledge. Best-in-class for sub-30B models.

Updated from model card. Dense 31B instruction-tuned.

Strong knowledge benchmark. Competitive with top models.

Open-weight MoE with 11B active params. Strong general knowledge for its size.

Solid general reasoning for a 13B-active MoE. Competitive with much larger models.

MoE with 3.8B active params. Strong efficiency.

9B params beating GPT-OSS-120B (80.8). Best-in-class for small open models.

Strong general knowledge, but trails Gemini 3.1 Pro and GPT-5 on this benchmark.

India's first domestically-trained 105B model. MoE with 10.3B active params. Apache 2.0.

48B MoE, 2.7B active params. Competitive with 9B-class models at fraction of compute.

17B active params, 128 experts, 400B total. Instruction-tuned score from official model card.

Broad knowledge and reasoning. Anthropic official benchmarks page.

Strong general knowledge for a 4B open-weight model.

Hybrid MoE model, 30B params with 3B active. Mamba-Transformer architecture with 1M token context. Open-weight under NVIDIA license.

Efficient small model. Competitive with much larger models using less compute.

SFT+RL variant. 14B params, MIT license, 32k context.

Instruction-tuned score from official model card.

14B dense model, MIT license. Strong for its size class.

Official model card score. Up from 60.0% (tweet source).

Ultra-compact 2.3B active params (5.1B total) with PLE. Fits in 1.5GB quantized. Strong for its size class.