Best Zhipu GLM Alternatives in 2026

Qwen3.6-27B delivers frontier-adjacent coding performance in 16.8 GB, it fits on an RTX 4090 and outperforms its 397B predecessor. Apache 2.0 across the full open-weight family makes it the cleanest-licensed Chinese LLM for commercial use in 2026.

MiniMax is a Shanghai-based AI lab offering a series of frontier text models, from the 456B-parameter M1 to the M2.7 flagship. Known for 1M-token context, open Apache 2.0 weights, and strong agentic coding at pricing well below Western alternatives.

Gemma is Google DeepMind's family of open-weight language models, downloadable and self-hostable for free. Gemma 4 (April 2026) delivers frontier-level reasoning and multimodal capabilities under an Apache 2.0 license, from 2B edge models to a 31B dense flagship.

AI21 Jamba is a hybrid Mamba-Transformer model family built for long-context enterprise tasks. Open-weight models run free on your own hardware; the API starts at $0.20 per million tokens with a genuine 256K context window.

Microsoft's Phi family proves data quality beats scale. The Phi-4 generation (14B, MIT license) punches above its weight on math and reasoning, and runs on consumer hardware. Free to download, with paid hosted inference on Azure AI Foundry.

OLMo is AI2's fully open language model family, releasing not just weights but the complete Dolma training dataset, all training code, and intermediate checkpoints under Apache 2.0. The research community's go-to for reproducible, auditable LLM science.

DeepSeek offers frontier-level reasoning and coding performance at API costs 10–30x cheaper than GPT-4o. The tradeoff is real: political censorship on the hosted product, PRC data residency, and a documented database exposure. Open weights mean local deployment is possible, at a price.

Moonshot AI's Kimi K2.6 is the open-weight model that quietly powered Cursor's Composer 2, tops SWE-Bench Pro at 58.6%, and supports 300-agent autonomous swarms, at a fraction of Claude Sonnet's per-token cost. Verbosity, hallucination rate, and language-dependent censorship are the real limits.

Llama is Meta's family of open-weight language models, from the 2023 originals through Llama 4's multimodal MoE releases. Free to download and self-host, the models power thousands of derived tools and enterprise pipelines worldwide.

vLLM is an open-source LLM inference library from UC Berkeley that delivers high-throughput, memory-efficient serving for hundreds of open models. Free under Apache 2.0, with an OpenAI-compatible API and support for multi-GPU deployments.