---

license: apache-2.0

base_model:

- NoemaAI-labs/Noema-2B

base_model_relation: quantized

language:

- en

library_name: gguf

pipeline_tag: text-generation

tags:

- noema

- qwen3.5

- gated-deltanet

- gguf

- llama.cpp

- quantized

- reasoning

- math

---

Noema-2B — GGUF

GGUF builds of NoemaAI-labs/Noema-2B,

a ~2B reasoning model post-trained from Qwen/Qwen3.5-2B

(hybrid Gated-DeltaNet architecture), for use with llama.cpp and

compatible runtimes.

For the full model description, benchmarks, training recipe, and

limitations, see the base model card.

⚠️ Requires Qwen3.5 (qwen35) architecture support in llama.cpp

This model uses the Qwen3.5 hybrid Gated-DeltaNet architecture. It

will only load in a llama.cpp build that includes the qwen35

architecture (linear + full attention layers). On an older

build you will get an "unknown architecture" / unsupported-arch error.

Use a recent llama.cpp with Qwen3.5 support and build from source if

your package manager's version is too old.

Files

| File | Quant | Size | Notes |

|---|---|---|---|

| Noema-2B-F16.gguf | F16 | 3.5 GB | Full precision; conversion reference. |

| Noema-2B-Q8_0.gguf | Q8_0 | 1.9 GB | Near-lossless; highest-fidelity quant. |

| Noema-2B-Q6_K.gguf | Q6_K | 1.5 GB | Very high quality, small quality loss. |

| Noema-2B-Q4_K_M.gguf | Q4_K_M | 1.2 GB | Recommended quality/size balance. |

All quants were produced from the same F16 conversion of the release

weights and smoke-tested (load + generation) on each file.

Usage

Noema is tuned and evaluated in non-thinking mode, which is the

default the embedded chat template applies. Pass --jinja so that

template is used, and the model runs in its trained (non-thinking) regime

automatically — no extra flags or prompt tags are needed.

Recommended sampling (the config Noema was evaluated under):

--temp 0.7 --top-p 0.8 --top-k 20 --presence-penalty 1.5.

Avoid --temp 0 / greedy decoding — this model family is documented

to enter repetition loops under greedy sampling.

# One-shot, single-turn (non-thinking):
llama-cli -m Noema-2B-Q4_K_M.gguf --jinja -cnv -st \
  -p "A farmer has 17 red apples and 25 green apples. How many in total?" \
  -n 256 --temp 0.7 --top-p 0.8 --top-k 20 --presence-penalty 1.5

# Or run an OpenAI-compatible server (set the sampling params client-side,
# or pass the same flags here as server defaults):
llama-server -m Noema-2B-Q4_K_M.gguf --jinja -c 4096 \
  --temp 0.7 --top-p 0.8 --top-k 20 --presence-penalty 1.5

License

Apache-2.0, inherited from the Qwen/Qwen3.5-2B base model.