Frontier intelligence,
specialized for your use case.

Training Jobs

qwen-math-grpo-livejob_grpo_math_
running

Qwen/Qwen3-4BGRPO7/10/2026

2× H100-80GBvast

Cost$9.7100
Duration120.0 min
Progress820/1200
Loss0.1837
View metrics in W&B
llama-support-sftjob_sft_suppor
queued

meta-llama/Meta-Llama-3-8B-InstructSFT7/10/2026

1× A100-80GBvast

Train models on your data.
Built for teams that need specialized models,
Veri handle all the infrastructure complexity.

Start training with only a few lines of code.

Ship a live model endpoint without managing a cluster.

Train effortlessly.

Bring your own dataset and kick off a run in a few lines. Veri provisions the exact GPU config, handles checkpointing, and streams logs end to end.

Training guide

Deploy peacefully.
Save massive.

Specializing a small open model on your task and it can match frontier quality at a fraction of the inference cost.

We provide an OpenAI compatible endpoint for deployed models, so you could seamlessly switch.

Deployment guide

Scale up without
the complexity

Some curated demos from us to help you get started using our platform.

Meant to be
easy.

Run an experiment in a few lines of code with the Veri SDK, then compare results before they reach production.

SDK
from veri_sdk import training_job@training_job(    base_model="Qwen/Qwen2.5-0.5B-Instruct",    dataset="hf:openai/gsm8k",    gpu_type="L4-24GB",    gpu_count=1,)def reward(completions, answer, **kwargs):    return [1.0 if a in str(c) else 0.0            for c, a in zip(completions, answer)]

Maximize Capability.

Iterate faster.

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