VibeThinker — WeiboAI 的本地 AI 模型
作者： Jakub Rusinowski · 最后更新：
MIT-licensed reasoning fine-tunes that argue the case for small models: VibeThinker-3B scores 94.3 on AIME26, matching what DeepSeek V3.2 reaches at 671B. Trained with the Spectrum-to-Signal pipeline — explore solution diversity during SFT, then reinforce the correct signal with RL. Vendor-reported and contested; treat the headline comparison as a claim about a narrow benchmark family, not general capability.
变体
VibeThinker 最小的变体在 Q4_K_M 下约需 2 GB 显存——量化权重加框架开销，不含 KV 缓存。
| 模型 | Q4 下显存 | 显存 | 上下文 | 运行 |
|---|---|---|---|---|
| VibeThinker 3B → 3B | ~2.7 GB | 131,072 | ollama run vibethinker | |
| VibeThinker 1.5B → 1.5B | ~1.7 GB | 131,072 | ollama run vibethinker |
显存为 Q4_K_M 下的量化权重加开销，与 GPU 与显存检测器使用同一引擎计算。
如何在本地运行 VibeThinker
安装 Ollama，然后拉取标签。
ollama run vibethinker在上方选择一个尺寸，查看它自己的显存、速度估算和安装命令。
许可证
Commercial use permitted. No usage restrictions beyond attribution.
适用于: VibeThinker 3B, VibeThinker 1.5B推荐 GPU
目录中能在本地运行 VibeThinker（至少 2 GB 显存）的最便宜 GPU 是 Intel Arc B570 (10 GB).
我的 GPU 能运行 VibeThinker 吗？
VibeThinker — 常见问题
How much VRAM does VibeThinker need?
VibeThinker needs about 2 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: VibeThinker 3B (3 GB, Q4_K_M); VibeThinker 1.5B (2 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run VibeThinker on an RTX 4090 (24 GB)?
Yes — VibeThinker runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for VibeThinker?
Q4_K_M is the best balance of quality and VRAM for VibeThinker in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run VibeThinker with Ollama?
VibeThinker has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.