DeepSeek on OpenGradient
DeepSeek v4 is frontier-grade reasoning at open-model prices - and using the official app means your prompts travel with your identity. Here the flash and pro variants run behind the anonymity layer: the relay knows who you are but not what you asked; the enclave knows the question but not the asker.
Free messages to start · no card · no identity attached
The usual way has a catch
DeepSeek is open-weights - which traditionally means either serious GPU hardware at home or a developer API with keys and payloads. The steerability is the point; the setup is the tax.
Consumer GPUs cap you at small quantized variants; the flagship sizes need datacenter hardware. Cloud APIs solve compute and reintroduce accounts, keys and logs.
Hosted access normally attaches your account to every prompt. The anonymity layer here splits identity from content - structurally, not by policy.
In the picker right now
Here's how OpenGradient is different
The full-size models - not the quantized compromises - served from the studio picker alongside every other family, switchable mid-conversation.
Neutrally-aligned open models that follow instructions instead of moralizing - no jailbreak prompts, no permission dance, within the published content policy.
Encrypted relays and secure enclaves ensure no party - including us - holds both your identity and your prompts.
Read the architectureFree messages to start · no card · no identity attached
The anonymity layer
Not a policy promise - a protocol. No single party, including us, ever holds both your identity and your question.
Read the full security architectureMessages are encrypted locally before they leave your browser.
Network relays split who you are from what you're asking. No one sees both.
The model reads your prompt inside attested hardware that never learns who sent it.
Questions, answered
Free to start, no card. Pick the model from the chips above and ask your first question in under a minute.