Model · Text generation
NVIDIA
Dec 2025 \- Jan 2026 September 2024 The pretraining data has a cutoff date of September 2024\. NVIDIA-Nemotron-3-Nano-4B-BF16 is a small language model (SLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the…
Open weights
other
4B parameters
262,144 tokens
transformers
An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 64 of RL run seededrlbaseramp25stoppengen4kep2ncp5n3ncvs16. - This is the best checkpoint by pass@8 so far in this run. Trained and validated on the cobalt-train ≤2/64 frontier (canonical cleaneval prompts): 1833 train / 112 held-out val problems the base model solved on at most 2 of 64 samples under the iidcanonical@64 hardness scan. Val evals sample at temperature 1.0 (matching the cleaneval frontier eval). Reward signal: binary code-correctness (1.0 if the generated program passes the problem's tests, otherwise 0.0). This checkpoint is the main revision (git branch) of the repo, with the model at the…
Open weights
4B parameters
262,144 tokens
transformers
An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 68 of RL run seededrlbaseramp25stoppengen4kep2ncp5n3nciid16. - This is the best checkpoint by pass@8 so far in this run. Trained and validated on the cobalt-train ≤2/64 frontier (canonical cleaneval prompts): 1833 train / 112 held-out val problems the base model solved on at most 2 of 64 samples under the iidcanonical@64 hardness scan. Val evals sample at temperature 1.0 (matching the cleaneval frontier eval). Reward signal: binary code-correctness (1.0 if the generated program passes the problem's tests, otherwise 0.0). This checkpoint is the main revision (git branch) of the repo, with the model at the…
Open weights
4B parameters
262,144 tokens
transformers
An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 90 of RL run seededrlbaseramp25stoppengen4kep2ncp5n3ncgroot16. - This is the best checkpoint by pass@8 so far in this run. Trained and validated on the cobalt-train ≤2/64 frontier (canonical cleaneval prompts): 1833 train / 112 held-out val problems the base model solved on at most 2 of 64 samples under the iidcanonical@64 hardness scan. Val evals sample at temperature 1.0 (matching the cleaneval frontier eval). Reward signal: binary code-correctness (1.0 if the generated program passes the problem's tests, otherwise 0.0). This checkpoint is the main revision (git branch) of the repo, with the model at…
Open weights
4B parameters
262,144 tokens
transformers
An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 56 of RL run seededrlbaseramp25stoppengen4kep2ncp5n3ncbase. - This is the best checkpoint by pass@8 so far in this run. Trained and validated on the cobalt-train ≤2/64 frontier (canonical cleaneval prompts): 1833 train / 112 held-out val problems the base model solved on at most 2 of 64 samples under the iidcanonical@64 hardness scan. Val evals sample at temperature 1.0 (matching the cleaneval frontier eval). Reward signal: binary code-correctness (1.0 if the generated program passes the problem's tests, otherwise 0.0). This checkpoint is the main revision (git branch) of the repo, with the model at the…
Open weights
4B parameters
262,144 tokens
transformers
Model · Text generation
H2O.ai
H2O-Lightning-4B-Nemotron-Nano is a 4B-parameter decision model from H2O.ai, built on nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16. It answers typed decision questions about a record (a document, a ticket, a policy, a conversation). It returns a probability for - yes/no (noul): gives the probability that a statement is true; It reads text only. It runs on unmodified vLLM 0.30.0 with a small shim in front (lightningnemo4bshim.py). Each decision is one forward pass and one output token, so the cost is input tokens only. card. Every measurement on this card is this model's own. Measured with serve.sh as shipped (vLLM 0.30.0; one temperature, 0.75, for every question type), on one NVIDIA H100 80GB…
Open weights
other
4B parameters
262,144 tokens
transformers