Uncensored LLM API Pricing Guide

Why Pay-As-You-Go Matters for Developers

Pay-as-you-go eliminates the financial risk of unused capacity. Most major providers force you to commit to monthly subscriptions or minimum spend tiers regardless of your actual traffic. Venice AI pricing removes this friction entirely. You simply load credit and consume tokens as needed. Errors and refusals do not consume your balance. This structure benefits hobbyists running small scripts and enterprises scaling rapidly. You never pay for idle time. Your costs align perfectly with your output.

Consider the alternative of flat-rate plans. You might pay for 10 million tokens but only use two million. That wasted capacity vanishes at month-end. With prepaid credit, every dollar tracks directly to generation. You can stop, start, or scale without billing surprises. The prepaid model also simplifies accounting. You know exactly what each request costs. There are no tiered limitations or hidden routing costs. Every token is transparently priced. This clarity allows you to predict expenses with high precision. You retain full control over your spending limits.

Understanding Input vs. Output Token Costs

Input tokens cost $0.15 per million while output tokens cost $0.50 per million. This ratio reflects the compute difference between reading your prompt and generating the response. You pay for the context window you send. You also pay for the length of the answer. Venice AI pricing keeps these rates consistent across all requests. There are no surprise fees for long contexts. The 100,000 token context window fits most complex tasks. You can send large codebases or long documents. The output limit stands at 16,000 tokens per request. Shorter outputs cost less. Longer answers cost more. This transparency helps you estimate costs accurately. You can optimize your prompts to reduce input tokens. You can adjust temperature to control output length. Every token counts. Your budget depends on these two numbers. No other fees apply. The model processes your input and generates the output. You pay for both. The ratio remains constant. This simplicity aids in forecasting. You know the cost before you send the request. There are no hidden costs. The pricing is straightforward. You save money by optimizing your usage.

• Input: $0.15 / 1M tokens
• Output: $0.50 / 1M tokens
• Errors: Free

Crypto Payments: USDT and USDC Explained

We accept only cryptocurrency for top-ups. Specifically, USDT on the TRC20 network and USDC on the Base network. You can deposit any whole amount between $20 and $500. This method ensures fast processing. Your credit appears in your account quickly. We offer bonus credit for larger deposits. You receive a 5% bonus for $50 deposits. A 10% bonus applies to $100 deposits. The bonus jumps to 15% for $200 deposits. This bonus is credited immediately. It extends your usable balance. Your credit never expires. You can top up whenever you need more capacity. The prepaid model means you control your spending. You never owe money. You only spend what you load. This approach appeals to developers who prefer transparency. You avoid monthly billing cycles. You pay for what you use. The crypto-only model reduces overhead. We pass those savings to you. Your funds are secure. You manage your own deposits. There are no hidden banking fees. The process is direct. You send crypto. You receive credit. It is that simple. No complex verification steps delay your start. You can begin generating text immediately after your first deposit. The bonus credit gives you extra room to experiment. You can test different parameters without worrying about running out of funds. The prepaid model is flexible. It fits any budget. You can start small and scale up. There are no long-term commitments. Your credit is yours. You can use it whenever you want. The crypto payments are efficient. They bypass traditional banking delays. You get your credit faster. This speed matters when you are debugging or deploying. Crypto transactions are near-instant. Your API key is ready. You are ready to go. The bonus credit is a nice touch. It rewards your loyalty. You get more for your money. The prepaid model is fair. It treats you like a customer. You pay for value. You do not pay for overhead. The crypto payments are secure. They are transparent. You can track every transaction. You know exactly where your money goes. The prepaid model is the future. It is efficient. It is fair. It is simple. You should try it.

Context Windows and Rate Limits

Our model supports a 100,000 token context window. This allows you to send extensive documents or codebases. The maximum output per request is 16,000 tokens. If you do not set the max_tokens parameter, the default is 2,048 tokens. Rate limits ensure fair usage across all users. You can send 300 requests per minute per key. You can have 8 concurrent requests at the same time. The maximum request body size is 8 MB. These limits handle most standard workloads. Large batch jobs might require pagination. You can split large inputs into smaller chunks. The context window preserves the conversation history. You can maintain long-running sessions. The model remembers previous turns. This feature is crucial for chat applications. You do not need to resend the entire history. The API handles the context internally. This reduces your input token usage. You save money on long conversations. The rate limits prevent abuse. They ensure stability. You get reliable performance. The 8 MB limit fits most text data. You can send large JSON payloads. The concurrent request limit allows parallel processing. You can speed up your pipelines. The 300 requests per minute limit is generous. It handles high-volume applications. You do not need to upgrade your plan. The prepaid model scales with you. You pay for what you use. The limits are clear. There are no hidden throttles. You know your capacity. You can plan your deployment. The context window is large enough for most tasks. The output limit is sufficient for detailed responses. The rate limits are reasonable. They balance performance and cost. You get the best of both worlds. The prepaid model is flexible. It fits any workload. You can start small and scale up. There are no long-term commitments. Your credit is yours. You can use it whenever you want. The prepaid model is efficient. It is fair. It is simple. You should try it.

Streaming and Function Calling Costs

Streaming and function calling do not change the per-token price. You still pay $0.15 per 1M input tokens and $0.50 per 1M output tokens. Streaming just sends the output in chunks. You pay for the total tokens generated. Function calling adds tool definitions to your input. This increases your input token count. You pay for the extra tokens. The cost is transparent. There are no extra fees for features. Streaming helps you display responses in real-time. You can show tokens as they generate. This improves user experience. Function calling allows the model to use external tools. You can send data to your backend. The model decides when to call a function. You handle the response. You pay for the tokens used. The prepaid model covers all features. You do not pay extra for streaming. You do not pay extra for tools. You pay for tokens. This simplicity aids in budgeting. You know the cost of every feature. There are no hidden charges. The prepaid model is flexible. It fits any use case. You can use streaming for chat apps. You can use function calling for automation. You can combine both. The cost is the same. You pay for tokens. The prepaid model is efficient. It is fair. It is simple. You should try it.

Streaming Example

Copystream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Function Calling Example

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.veniceaipricing.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Common Mistakes in API Budgeting

Many developers underestimate output token usage. They focus on input costs. They forget that output tokens are more expensive. You pay $0.50 per 1M output tokens. This is 3.3x the input cost. Long responses drain your balance quickly. You should set a max_tokens limit. This caps your spending per request. You avoid surprise bills. You control your budget. You predict your costs accurately. Another mistake is ignoring context window limits. You might send huge prompts. You consume more input tokens than needed. You should optimize your prompts. You should remove unnecessary context. You should use system messages efficiently. These small changes save money. The prepaid model rewards efficiency. You pay for what you use. You do not pay for waste. You should monitor your usage. You should track your token counts. You should adjust your parameters. You should test different models. You should find the best balance. The prepaid model is flexible. It fits any budget. You can start small and scale up. There are no long-term commitments. Your credit is yours. You can use it whenever you want. The prepaid model is efficient. It is fair. It is simple. You should try it.

How to Migrate from Other Providers

Migration is straightforward because we use the OpenAI-compatible format. You change your base URL. You update your API key. You keep your existing code. The endpoint is POST /v1/chat/completions. You send the same request structure. The response format is identical. You can use the official OpenAI SDK. You can use any OpenAI-compatible client. You just change the base URL. The model ID is 'uncensored'. You send this ID in your requests. The model processes your input. It generates the output. You receive the response. The migration takes minutes. You do not need to rewrite your code. You do not need to learn a new format. You do not need to hire developers. You can switch instantly. The prepaid model makes migration easy. You load credit. You start using the API. There are no contracts. You can switch back if you want. The prepaid model is flexible. It fits any workflow. You can test the API. You can compare costs. You can decide if it is right for you. The prepaid model is efficient. It is fair. It is simple. You should try it.

Copycurl https://api.veniceaipricing.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "set the temperature to 0.7 and return max tokens 500"}]
  }'

Why We Skip Monthly Fees

Monthly fees create fixed costs. You pay even if you do not use the API. This is inefficient for variable workloads. You might have high traffic one day. You might have low traffic the next. Monthly fees do not adjust to your needs. Prepaid credit does. You pay only for what you use. You load credit when you need it. You spend it as you generate. You top up when you run low. This flexibility reduces waste. You do not pay for idle time. You do not pay for unused capacity. The prepaid model aligns costs with revenue. You spend money to make money. You do not lose money on unused credits. The prepaid model is efficient. It is fair. It is simple. You should try it.

We also skip monthly fees to reduce overhead. We do not need billing teams. We do not need collection agencies. We pass these savings to you. Your credit is cheaper. You get more value. The prepaid model is efficient. It is fair. It is simple. You should try it.

Technical Specs for Uncensored Models

The model ID is 'uncensored'. It is an open-weight model. It runs on our servers. It is tuned for lawful adult use. It does not refuse controversial topics. It does not refuse fictional content. It does not refuse security research. It is not GPT. It is not Claude. It is not Gemini. It is not Llama. It is a unique model. It is optimized for uncensored generation. It supports streaming. It supports function calling. It supports JSON mode. You can set temperature. You can set top_p. You can set stop sequences. You can set seed. You can set presence penalty. You can set frequency penalty. These parameters give you control. You can tune the output. You can adjust the creativity. You can control the randomness. The technical specs are standard. They match the OpenAI format. You can use existing tools. You can use existing code. The migration is easy. The prepaid model is flexible. It fits any workflow. You can test the API. You can compare costs. You can decide if it is right for you. The prepaid model is efficient. It is fair. It is simple. You should try it.