Overclock: Flat-Rate Inference for Coding Agents

Research context and background

Overclock is a specialized API platform built for coding agents. It offers a flat-rate inference model designed to eliminate the unpredictability of token-based billing. Instead of paying per token, users pay for parallel capacity, making it ideal for long-running, iterative agent workflows.

Benefits

Overclock solves the financial uncertainty that traditional metered pricing models create for AI agents. With standard rates, a heavy eight-hour agent day could cost over $125 per month. Overclock removes the meter entirely by using a buy runners not tokens philosophy. A runner is a single job slot, and users are billed based on how many runners they run simultaneously, not on how much work they perform. Each runner handles one request at a time regardless of duration or token consumption. Extra work queues up instead of failing or dropping. Running multiple agents simply means adding more runners, not increasing the invoice. The platform guarantees a context window of 260K+ tokens to accommodate full agent sessions. It also targets a generation rate of 40+ tokens per second and a time to first token of under five seconds for 95% of requests. Overclock manages a smart pool of models, routing requests to the best-suited available option without requiring users to pick a specific model. Every model in the pool must score above 70% on Terminal-Bench 2.1 or 50+ on the Artificial Analysis Intelligence Index. Users always receive the newest public version of the model serving their request. The platform is OpenAI- and Anthropic-compatible, allowing it to plug directly into existing coding agent setups without infrastructure changes.

Use Cases

Overclock is designed for developers running long-running agent workloads. It is ideal for scenarios involving retries, long tool calls, or extended sessions where token-based billing would create high costs. The platform supports various agents and frameworks including Cline, Roo Code, Hermes, OpenClaw, Aider, Continue.dev, Claude Code, OpenAI SDK, LangChain, LlamaIndex, LiteLLM, and n8n. Teams can use it to build robust automation by focusing on their work without worrying about financial friction from extended processing times. The self-serve access allows users to sign up via email or Google without needing a card to start. Users can select a plan, get their API key instantly, and configure their environment to begin using the service.

Pricing

Plans start at $15 per month and scale based on the number of concurrent runners. The Single plan costs $15 per month and includes one runner with OpenAI and Anthropic compatibility, a model ID of redline, a 260K+ context window, and unlimited tokens while active. The Stack plan costs $29 per month and includes two jobs in flight for real parallel work along with all Single features. The Workshop plan costs $49 per month and includes four jobs in flight for heavier automation loads along with all Stack features. All plans offer unlimited tokens while active. Extra parallelism beyond the runner count requires adding more runners.

Vibes

Overclock provides a stable and predictable billing model for developers. By decoupling cost from token usage and tying it instead to parallel capacity, it removes the financial friction of retries and extended processing times. This allows teams to focus on building robust automation without the worry of unexpected monthly bills. The platform ensures that users always have access to the latest model versions and maintains a high quality floor for all models in its pool. The ease of integration and self-serve access further enhances the user experience for developers looking to implement coding agents efficiently.

Additional Information

Overclock is a self-serve platform with no waiting periods for access. Users can create an account via email or Google, select a plan, and receive their API key instantly upon payment clearance. The configuration process involves setting the base URL, key, and model ID in the environment. The platform supports a unified model ID of redline for all requests. The service guarantees specific performance metrics to ensure agents run smoothly, including a guaranteed context window and targeted generation rates. The model pool includes models from DeepSeek, Gemini, GLM, GPT, Luna, Muse, and Spark. Updates are automatic, ensuring users always have the newest public version of the model serving their request.