Alternatives to Edge0

Zhipu's first natively multimodal GLM (confirmed as the 'Ox Alpha' stealth model): 320B MoE with 18B active, 1M context, MIT open weights at $0.15/M input.

NVIDIA's efficient open-weight 30B MoE hybrid model with 3B active parameters, 1M-token context, and single-GPU deployment for local reasoning and coding.

DeepSeek-V4.1-Flash is a MIT 552B multimodal MoE with 8B/16B activation, 1M context, and about 1/4 the KV cache of V4-Flash.

DeepSeek flagship 1.6T MoE with 49B active, 1M context, MIT weights. API $0.29/$1.20 cached $0.03.

Ling-3.0-flash is inclusionAI's MIT-licensed hybrid reasoning model with a hybrid-linear MoE design, 124B total and 5.1B active parameters.

Ling-3.0-tiny is inclusionAI's MIT hybrid-linear MoE: 7.9B total, 1.3B active, for local agents.

Nex-N2.5-mini is Nex-AGI's Apache-2.0 multimodal agent model for computer use, browsing, and coding.

Nex-N2.5-Pro is Nex-AGI's Apache-2.0 multimodal agent checkpoint for computer use, browsing, and coding.

Alibaba's open-weight architecture preview of Qwen4: 125B multimodal MoE with 6B active plus a 51B N-gram table, 262K native context, at $0.16/M input.

Spark-X2.5-4B is XHToken's compact Apache-2.0 open-weight model, using hybrid sliding-window attention for a native 1M-token context and strong coding.

DeepSeek small agent model: 284B/13B MoE, 1M context, MIT weights, $0.14/$0.28 per 1M tokens.

Poolside's open-weight 118B MoE coding model with 8B active parameters, a 1M-token context window, native interleaved reasoning, and an OpenMDW-1.1 license.

Ling-3.0-flash-VL is inclusionAI's MIT multimodal MoE: 124B total, 5.5B active, with image and video.

Meituan's open-weight MoE model: 1.6T total / ~48B active params, 1M context, MIT. Strong on coding and agentic tasks (2026-08-25).