Models & Pricing

Hosted Training supports a range of open-weights models. This page lists the currently available models, their pricing, and guidance on choosing the right model for your use case.

Available Models

Prices are per million tokens, billed separately for input, output, and training.

Model	Input ($ / 1M)	Output ($ / 1M)	Train ($ / 1M)
`Qwen/Qwen3.5-0.8B`	0.02	0.06	0.06
`Qwen/Qwen3.5-2B`	0.05	0.15	0.15
`Qwen/Qwen3.5-4B`	0.10	0.30	0.30
`Qwen/Qwen3.5-9B`	0.20	0.60	0.60
`Qwen/Qwen3.5-35B-A3B`	0.25	0.75	1.00
`Qwen/Qwen3.6-35B-A3B`	0.25	0.75	1.00
`meta-llama/Llama-3.2-1B-Instruct`	0.02	0.06	0.06
`meta-llama/Llama-3.2-3B-Instruct`	0.05	0.15	0.15
`nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16`	0.15	0.45	0.60
`nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16`	0.30	0.90	1.20
`openai/gpt-oss-20b`	0.10	0.30	0.40
`openai/gpt-oss-120b`	0.25	0.75	1.00
`poolside/Laguna-XS.2`	0.00	0.00	0.00
`sprints/Llama-3.2-1B-Instruct`	0.00	0.00	0.00

Choosing a Model

For Validation and Debugging

Start with a small, fast model to verify your environment and config work correctly before committing compute to a larger run. Recommended: Qwen/Qwen3.5-0.8B or meta-llama/Llama-3.2-1B-Instruct

model = "Qwen/Qwen3.5-0.8B"
max_steps = 50
batch_size = 128
rollouts_per_example = 8

For Experimentation

MoE models with small active parameter counts give strong performance per token. Recommended: Qwen/Qwen3.5-35B-A3B

model = "Qwen/Qwen3.5-35B-A3B"
max_steps = 200
batch_size = 256
rollouts_per_example = 16

For Production Training

For serious training runs where you want the strongest possible results, use the larger MoE models. Recommended: nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16

model = "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16"
max_steps = 500
batch_size = 512
rollouts_per_example = 16

Thinking Mode

Qwen3.5 and Nemotron models support a thinking mode that produces extended chain-of-thought reasoning before the final answer. Toggle it via [sampling].enable_thinking in your config. Thinking mode tends to help on tasks that benefit from multi-step reasoning (math, code, logic) at the cost of longer outputs.

Checking Available Models

Always use the CLI to check the current list of supported models:

prime train models

Add --output json to get the live pricing alongside the model list. This may differ from this page as models are being added regularly.

Full Fine-Tuning Troubleshooting

⌘I

Getting Started

Lab

Libraries

Compute

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

prime-rl

Available Models

Choosing a Model

For Validation and Debugging

For Experimentation

For Production Training

Thinking Mode

Checking Available Models

​Available Models

​Choosing a Model

​For Validation and Debugging

​For Experimentation

​For Production Training

​Thinking Mode

​Checking Available Models

Available Models

Choosing a Model

For Validation and Debugging

For Experimentation

For Production Training

Thinking Mode

Checking Available Models