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OpenAI fine-tuning is gone. We're not.

The fine-tuning API
for developers.

Upload your training data, pick a model — Llama, Mistral, Gemma — get a hosted inference endpoint. No infrastructure, no ML team, no Python required.

fine-tune.ts
import { Turing } from "@turing-compute/sdk";

const client = new Turing({ apiKey: process.env.TURING_API_KEY });

// 1. Upload your training data
const file = await client.files.upload("./data/training.jsonl");

// 2. Start a fine-tuning job on any open-source model
const job = await client.fineTuning.create({
  model:          "meta-llama/Llama-3.1-8B-Instruct",
  trainingFile:   file.id,
  suffix:         "support-classifier-v1",
});

// 3. Poll until ready — or listen via webhook
await client.fineTuning.waitForCompletion(job.id);

// 4. Use your hosted endpoint immediately
const response = await client.chat.completions.create({
  model:    job.endpoint,
  messages: [{ role: "user", content: "Is this a billing question?" }],
});

console.log(response.choices[0].message.content);
#1

TypeScript is the top language on GitHub (2025 Octoverse)

$100M+

ARR validated by Together AI — the fine-tuning market is real

3

GPU providers behind every job: Together AI, Fireworks, Replicate

How it works

Train to deployed endpoint
in three steps.

Every competitor separates fine-tuning from inference. Turing ships them together — the endpoint is ready when training finishes.

Upload your training data

Drop a JSONL file with your examples. Use any chat-completion format — the same structure you already send to OpenAI.

Supports JSONL · Up to 1 GB · Automatic validation

Pick your base model

Choose from Llama 3.1, Mistral, Gemma 2, Qwen, and more. We route the job to the best available GPU provider transparently.

LoRA · Full fine-tuning · Quantization options

Get a hosted endpoint

Training completes, an inference endpoint spins up. Call it exactly like OpenAI — same client, same message format, your model.

OpenAI-compatible API · Auto-scaling · Pay per token

Why Turing

Built for the developer
who doesn't have an ML team.

TypeScript-first SDK

Every competitor is Python-first. Turing was designed from day one for the TypeScript and JavaScript ecosystem — typed responses, first-class async/await, and a client that feels native.

npm i @turing-compute/sdkFull type coverageNode · Deno · Bun

OpenAI drop-in replacement

The Turing endpoint speaks the OpenAI chat completions format. If you already call OpenAI, swapping the base URL and model ID is the entire migration.

Same message formatCompatible clientZero API redesign

No infrastructure to manage

No GPUs to provision, no CUDA drivers to configure, no inference servers to maintain. Turing routes training jobs to best-in-class providers and returns an endpoint when the work is done.

Together AIFireworks AIReplicate

Transparent, usage-based pricing

Pay for training tokens and inference tokens. No seat licenses, no enterprise tier gating access to the good models. Every feature is self-serve from day one.

Per-token billingNo minimumsFull self-serve

Supported models

Every major open-source
family. More added regularly.

You pick the model. We pick the best GPU provider for the job — transparently, with no lock-in to any single infrastructure vendor.

LlamaMeta
Llama 3.1 8BLlama 3.1 70BLlama 3.2 3BLlama 3.3 70B
MistralMistral AI
Mistral 7B v0.3Mistral Nemo 12BMistral Small 22B
GemmaGoogle
Gemma 2 2BGemma 2 9BGemma 2 27B
QwenAlibaba
Qwen 2.5 7BQwen 2.5 14BQwen 2.5 72B

Full model catalog at docs.turingcompute.com/models

Comparison

Same underlying compute.
Better developer experience.

Feature
Turing
Together
Fireworks
TypeScript-first SDK
Fine-tuning + hosted endpoint in one step
OpenAI-compatible inference endpoint
Fully self-serve, no sales motion
No minimum spend
Transparent GPU routing

Based on public documentation as of mid-2025. Subject to change.

Pricing

Transparent pricing.
No enterprise sales required.

Training and inference are billed separately, per token. No seat licenses, no tier gating on models, no minimum spend.

Starter
Free

up to $20 in training credits

Ideal for experiments and proof-of-concept fine-tunes.

  • 3 fine-tuning jobs / month
  • Up to 100K training tokens
  • Hosted endpoint — 7-day TTL
  • Community support
Start for free
ProPopular
Usage-based

pay only for what you train and infer

For production apps and teams shipping custom models.

  • Unlimited fine-tuning jobs
  • All models — including 70B+
  • Persistent hosted endpoints
  • Webhooks + TypeScript SDK
  • Email support
Start building

Fine-tune. Deploy. Done.

Your first fine-tuning job is on us. No credit card, no sales call, no infrastructure to provision.

npm i @turing-compute/sdk