Nemotron-3-Nano-30B-A3B with Hermes Agent
Q8_0 (GGUF) on llama.cpp commit a37cc46. Tested
Task completion
83.3% (25/30)
Tool-call success
72.3%
Decode tok/s
56.9
Prefill tok/s
3166.4
Server memory
31.7 GB
Avg turns
4.7
Setup
- Model
- Nemotron-3-Nano-30B-A3B
- Family / maker
- Nemotron · NVIDIA
- Parameters
- 30B (3B active)
- Architecture
- MoE
- Weights
- unsloth/Nemotron-3-Nano-30B-A3B-GGUF
- Quant
- Q8_0 (GGUF)
- Engine
- llama.cpp commit a37cc46
- Hermes Agent
- v0.22.4
- Tested
- 2026-10-23
- Context
- 64K (65,536 tokens); long-context task t09 at 128K or 192K
- Memory tier
- ≤128 GB (measured)
Per-task results
- t01: 3/3 · day run: 3/3
- t02: 3/3 · day run: 3/3
- t03: 3/3 · day run: 3/3
- t04: 3/3 · day run: 3/3
- t05: 3/3 · day run: 3/3
- t06: 3/3 · day run: 3/3
- t07: 1/3 · day run: 3/3
- t08: 2/3 · day run: 2/3
- t09: 1/3 (rerun 2026-10-23, 192K context) · day run: 0/3 (old harness, model never called)
- t10: 3/3 · day run: 3/3
First number: night run 2026-10-23 (shown in the stats above).
Copy-paste config
1. Start the model server (llama.cpp)
Exact command used in our test. Download the GGUF from unsloth/Nemotron-3-Nano-30B-A3B-GGUF into ./models/.
llama-server --model ./models/Nemotron-3-Nano-30B-A3B-Q8_0.gguf --alias nemotron-3-nano-30b-a3b --host 127.0.0.1 --port 18080 --ctx-size 65536 --parallel 1 --n-gpu-layers 999 --flash-attn on --jinja2. Point Hermes Agent at it
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:18080/v1
hermes config set model.default nemotron-3-nano-30b-a3bOther Nemotron setups
- Nemotron-Cascade-2-30B-A3B · Q4_K_M (GGUF) · llama.cpp
- Nemotron-3-Super-120B-A12B · NVFP4 · vLLM