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Tinker

Fine-tuning API for open-source LLMs

API
Jack Phillips
Audited by Jack Phillips · Updated May 2026
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Overall score

2.4/ 5
SME fit2/5
usage-metered pricing · technical setup
JTBD3/5
moderate JTBD clarity
Integration4/5
API + 7 integrations
Trust1/5
new (<12mo), founded 2025
Quality1/5
no public rating
Compliance2/5
compliance unknown

About

Tinker is a fine-tuning API from Thinking Machines Lab that lets engineers train custom models on top of Llama, Qwen, DeepSeek, GPT-OSS, Moonshot and Nemotron families without managing GPU infrastructure. LoRA-based by default for efficient training. Pay-as-you-go pricing per million tokens trained.

Best for: ML engineers and AI researchers who want to fine-tune open-source LLMs without managing GPU clusters or wiring distributed-training infrastructure themselves.

Pricing

  • Pay-as-you-go (small models)

    Monthly
    n/a
    Annual /mo
    n/a
    Billing
    usage_based
    Notes
    Llama 3.2 1B fine-tuning at $0.09/M tokens;LoRA training;Checkpoint download API;Self-serve API access · Smallest model tier. Cheap for prototyping fine-tunes.
  • Pay-as-you-go (large MoE)

    Monthly
    n/a
    Annual /mo
    n/a
    Billing
    usage_based
    Notes
    Qwen3.5-397B-A17B with 256K context at $12/M tokens;Storage $0.10/GB-month;Distributed training · Largest models tier. Limited-time 50% discount available on select NVIDIA models.

Key features

  • LoRA-based fine-tuning of open-source models
  • Wide model coverage (Llama, Qwen, DeepSeek, GPT-OSS, Moonshot, Nemotron)
  • Pay-as-you-go pricing per million tokens
  • Distributed training on GPU clusters abstracted away
  • Forward and backward pass + optimizer step + sampling primitives
  • Model checkpoint downloads via API

Integrations

LlamaQwenDeepSeekGPT-OSSMoonshot KimiNVIDIA NemotronHugging Face

Trust & compliance

Stage range
Seed → Growth
Founded
2025
Status
active
SOC 2
unknown
GDPR
unknown
Data residency
unknown
External rating
n/a
Last verified
May 2026

Reviews

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