Skip to content
Dagon Inference

Dagon Inference / Providers that host abliterated (refusal-removed) open-weight models through an API

Providers that host abliterated (refusal-removed) open-weight models through an API

Published · Last updated

abliteration.ai (abliterated-model-large-flash, abliterated-model, abliterated-model-large-v2), Refuseless (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated), Experiential Labs (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated), Lutheos (deepseek-v4.1-flash-abliterated) and Silk Compute (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated, kimi-k3.1-pro-abliterated) host refusal-removed (abliterated) open-weight models through an API, and Dagon Inference puts all of them behind one OpenAI and Anthropic compatible API at https://inference.dagon.so/v1: each request goes to the cheapest healthy provider for its model id, falls back to the next cheapest if that one fails before any output, and is billed per token in USDC with a signed receipt naming the provider. These are the providers Dagon Inference routes to, not a survey of every host.

Which abliterated models does each provider host?

ProviderModelModel idInputOutputEndpoints
abliteration.aiAbliterated Large Flashabliterated-model-large-flash$1.10$2.20Chat, Responses, Messages
abliteration.aiAbliterated Modelabliterated-model$1.10$3.30Chat, Responses, Messages
abliteration.aiAbliterated Large v2abliterated-model-large-v2$3.30$5.50Chat, Responses, Messages
RefuselessGLM-5.3 Abliteratedglm-5.3-abliterated$1.10$2.20Chat, Responses
RefuselessDeepSeek V4.1 Flash Abliterateddeepseek-v4.1-flash-abliterated$0.132$0.495Chat, Responses
RefuselessGLM-5.3 Flash Abliteratedglm-5.3-flash-abliterated$0.132$0.55Chat, Responses
Experiential LabsGLM-5.3 Abliteratedglm-5.3-abliterated$1.54$4.84Chat
Experiential LabsDeepSeek V4.1 Flash Abliterateddeepseek-v4.1-flash-abliterated$0.33$1.32Chat
Experiential LabsGLM-5.3 Flash Abliteratedglm-5.3-flash-abliterated$0.165$0.55Chat
LutheosDeepSeek V4.1 Flash Abliterateddeepseek-v4.1-flash-abliterated$0.11$0.44Chat, Messages
Silk ComputeGLM-5.3 Abliteratedglm-5.3-abliterated$2.20$4.40Chat, Responses, Messages
Silk ComputeDeepSeek V4.1 Flash Abliterateddeepseek-v4.1-flash-abliterated$0.308$1.10Chat, Responses, Messages
Silk ComputeGLM-5.3 Flash Abliteratedglm-5.3-flash-abliterated$0.264$1.10Chat, Responses, Messages
Silk ComputeKimi K3.1 Pro Abliteratedkimi-k3.1-pro-abliterated$5.50$16.50Chat, Responses, Messages

US dollars per 1M tokens through Dagon Inference: the provider's price plus the 10% markup, at price version 2026-11-11.4. A provider's own direct prices and terms may differ. Live: /v1/models.

Six ways a request ends
90123456789019012345678901901234567890190123456789019012345678901µ$90123456789019012345678901901234567890190123456789019012345678901456345456678234
Before forwarding, the gateway holds the worst case: 37,545 µ$ for a 1,200-character prompt to Large Flash (abliteration.ai) with the default 16,384-token cap. When the upstream reports its usage the charge is 724 µ$ and 36,821 µ$ is released; each other way a request can end has its own defined charge, and the register rolls to it as the selector turns. The tell-tale rises when the gateway signs and stores a receipt.

What is an abliterated model?

Abliteration edits an open-weight model's weights to remove the direction that drives refusals, so it needs a model whose weights are available: a closed model such as GPT or Claude cannot be abliterated by anyone outside its lab. The models above are labelled from our live probes, which show their refusal behavior as removed; individual requests may still be declined or answered poorly, and we have not benchmarked their quality. abliteration.ai's own abliterated build of GLM-5.3 is abliterated-model-large-v2; it is post-trained by abliteration.ai, so it can behave differently from glm-5.3-abliterated.

How do you reach every provider with one key?

Create a key with curl -X POST https://inference.dagon.so/v1/keys (no email or password), fund it with USDC from $5, and call any model id above at https://inference.dagon.so/v1 with an OpenAI SDK, or at https://inference.dagon.so with an Anthropic SDK (see the Anthropic Messages guide). The gateway picks the cheapest healthy provider serving the model on the endpoint you call; each model page lists every provider's price, and the pricing page has the whole table.

What do the providers say they keep?

abliteration.ai states that it does not store prompts or completions by default; Refuseless may pass requests to third-party providers it chooses, which it says generally operate under zero data retention; Experiential Labs says its models are not zero retention. Lutheos says its GPU partner keeps no prompts or replies; Silk Compute says it does not store prompts or outputs and serves its models without content filters. Cheaper Inference keeps request content unless the request asks for zero data retention; ours always do, and it says it then keeps none and sends the request only to providers that keep none. We cannot verify or control any of that.

We do not monitor or log your content, and the acceptable use policy applies: use it lawfully and only against systems and people you own or have permission to test. We suspend keys that break it.

Common questions

Which providers host refusal-removed (abliterated) open-weight models through an API?

abliteration.ai (abliterated-model-large-flash, abliterated-model, abliterated-model-large-v2); Refuseless (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated); Experiential Labs (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated); Lutheos (deepseek-v4.1-flash-abliterated); Silk Compute (glm-5.3-abliterated, deepseek-v4.1-flash-abliterated, glm-5.3-flash-abliterated, kimi-k3.1-pro-abliterated). Dagon Inference routes to all of them through one OpenAI and Anthropic compatible API at https://inference.dagon.so/v1, sending each request to the cheapest healthy provider for its model id, billed per token in USDC.

Are abliterated models fully uncensored?

Not guaranteed. Abliteration removes the direction in the weights that drives refusals, and our live probes show refusal behavior removed for the models above, but individual requests may still be declined or answered poorly. We do not monitor or log your content, and the acceptable use policy applies: use it lawfully and only against systems and people you own or have permission to test. We suspend keys that break it.

Can one key reach models from several providers?

Yes. One Dagon Inference key reaches every model above; a model served by several providers falls back to the next cheapest if one fails before any output, and each signed receipt names the provider that served the request.

Create a key in a minute.

Get a key