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Open-weight models ship with published weights and permissive licenses, so you can inspect them, self-host them, and avoid lock-in to a closed vendor. ZeroGPU serves five of them — for reasoning, coding, agentic workflows, and high-volume summarization — through the same OpenAI-compatible API as every other model in the catalog. Full request and response examples for each model live on the Text Generation page.

At a glance

Model cards

deepseek-v4-flash
deepseek-v4-flash
1,048,576 context window$0.16 / 1M input$0.38 / 1M output$0.006 / 1M cached input
DeepSeek’s DeepSeek-V4-Flash is an open-weight Mixture-of-Experts model built for efficient reasoning, coding, and agentic workflows, with 284B total parameters activating only 13B per token. Its…
glm-5.2
glm-5.2
1,048,576 context window$1.10 / 1M input$3.50 / 1M output$0.40 / 1M cached input
Z.ai’s GLM-5.2 is an open-weight Mixture-of-Experts flagship built for long-horizon tasks, with 753B total parameters activating 8 of 256 experts per token. It sustains a solid 1,048,576-token (1M)…
qwen3-30b-a3b-fp8
qwen3-30b-a3b-fp8
32,768 context window$0.05 / 1M input$0.30 / 1M output
Alibaba’s Qwen3-30B-A3B is an open-weight Mixture-of-Experts model with 30.5B total parameters (3.3B active per token), served on ZeroGPU as an FP8 build for efficient inference. It thinks through a problem…
gpt-oss-120b
gpt-oss-120b
131,072 context window$0.15 / 1M input$0.60 / 1M output
OpenAI’s gpt-oss-120b is an open-weight Mixture-of-Experts model with 117B total parameters (5.1B active per token), served on ZeroGPU for general text generation. It reasons through a problem…
llama-3.1-8b-instruct-fast
llama-3.1-8b-instruct-fast
131,072 max tokens$0.02 / 1M input$0.05 / 1M output
Meta’s Llama 3.1 Instruct, tuned for fast, low-cost summarization at scale on the ZeroGPU edge network. Its 128K-token context window takes in entire documents, long transcripts, and full email or…