Models on Brain Nodes.
| Model | Params | Min VRAM | License | Nodes online | Loaded | Speed | Lowest ask | Regions | Asked 24h | Served | Unserved | Status |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| qwen/qwen2.5-1.5b-instruct | 1.5B | 5.9 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-3b-instruct | 3B | 9.8 GB | Qwen Research | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-7b-instruct | 7B | 20 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-7b-instruct-awq | 7B | 9.8 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| mistralai/mistral-7b-instruct-v0.3 | 7B | 20 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| meta-llama/llama-3.1-8b-instruct | 8B | 20 GB | Llama 3.1 Community (gated; node needs HF_TOKEN) | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-14b-instruct | 14B | 33 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-14b-instruct-awq | 14B | 14 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-32b-instruct | 32B | 70 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-32b-instruct-awq | 32B | 23 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-coder-32b-instruct | 32B | 70 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-coder-32b-instruct-awq | 32B | 23 GB | Apache-2.0 | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-72b-instruct | 72B | 146 GB | Qwen (non-commercial above 100M MAU) | … | … | unmeasured | — | — | … | … | … | no nodes |
| qwen/qwen2.5-72b-instruct-awq | 72B | 47 GB | Qwen (non-commercial above 100M MAU) | … | … | unmeasured | — | — | … | … | … | no nodes |
| deepseek-ai/deepseek-r1-distill-qwen-32b | 32B | 70 GB | MIT | … | … | unmeasured | — | — | … | … | … | no nodes |
| deepseek-ai/deepseek-r1-distill-llama-8b | 8B | 20 GB | MIT (Llama 3.1 Community for the base weights) | … | … | unmeasured | — | — | … | … | … | no nodes |
| meta-llama/llama-3.3-70b-instruct | 70B | 146 GB | Llama 3.3 Community (gated; node needs HF_TOKEN) | … | … | unmeasured | — | — | … | … | … | no nodes |
| brain/mock mock | 0 | — | n/a | … | … | unmeasured | — | — | … | … | … | mock |
Speed is the median of coordinator-timed tokens per second on completed jobs for nodes currently serving the model; it reads unmeasured until a job has run. Asked / served / unserved are counts of customer orders naming the model in the last 24 h, from the order log; unserved means no node could take it or every attempt failed. Pricing: the network list price applies unless a node sets an ask; asks are a routing input and are shown on the node's provider page.
A request that names a model only ever goes to a node serving that model. Pin the ones you want to compete on and the router sends you that traffic, ranked against other nodes on capability, availability, measured latency, reputation and your ask price. Pinned models are advertised on registration and checked against what your server actually serves.
# vLLM (NVIDIA): the agent pulls and serves the pinned ids BRAIN_NODE_MODE=vllm BRAIN_NODE_MODELS=qwen/qwen2.5-32b-instruct-awq,qwen/qwen2.5-coder-32b-instruct-awq npm run node # Ollama / llama.cpp / mlx-lm / exo: serve the model yourself, pin what to advertise ollama pull qwen2.5:32b-instruct BRAIN_NODE_MODE=ollama BRAIN_NODE_MODELS=qwen/qwen2.5-32b-instruct npm run node # Optional: an ask price per 1M tokens; the router treats it as one input among five BRAIN_NODE_ASK_USD_PER_1M=0.40