Full 1M context V4-Flash without owning eight GPUs
热度趋势
趋势数据积累中
百分比基于当前可用热度信号，而非评论数或独立用户人数。
OpenAI 相关模型动态已经出现，适合跟踪能力变化、生态影响和后续可用性。
Gonka提供了一个去中心化的推理网络，用于运行V4-Flash模型，解决了在不拥有八个GPU的情况下运行其284B参数和1M上下文窗口的难题。它提供了一个与OpenAI兼容的解决方案，用户可以通过社区代理以常规支付方式访问完整的上下文窗口。这项服务填补了本地执行模型过大的空白，为用户提供了集中式端点之外的替代方案。…
Disclosure: posted by a Gonka contributor.
The practical problem with V4-Flash for this sub: 284B parameters at a 1M window. Most people here cannot run that, and the quantised builds that do fit give up most of the context, which is usually the reason the model was interesting in the first place. Gonka is a decentralized inference network serving V4-Flash across independent GPU hosts at the full context window. OpenAI-compatible, so it is a base URL swap in Ollama, LM Studio, Cline or anything else already in use. Access goes through a community broker and brokers take ordinary payment, so there is no wallet and no chain interaction involved. This is not a pitch to stop running local. Local is faster, private, and free at the margin, and it wins on all three for anything that fits. This is for the gap where the model does not fit and the alternatives are a centralised endpoint or nothing. What is different in that gap: supply comes from independent operators rather than reselling the same clouds as everyone else, so the price behaves differently, and nothing about the setup creates lock in. Code is open, including the coordination layer: https://github.com/gonka-ai/gonka
Endpoint: https://gonka.ai
Discord: https://discord.gg/ex3dw4wB
Happy to answer anything, including where it performs badly.