A powerful reasoning and coding model by xAI, optimized for agentic tasks and complex problem-solving via AIML API.
What exactly is Grok Build 0.1?
Grok Build 0.1 is xAI's reasoning and coding model built for agentic software development. It is designed to plan, write, debug, and iterate on code across multi-step tasks — operating as an autonomous coding agent rather than a single-turn code generator. The model supports function calling, tool use, and is fully OpenAI-compatible.
API Pricing
* Input: $1.30 / 1M tokens
* Output: $2.60 / 1M tokens
Architecture: what makes it capable
Reasoning-first designGrok Build 0.1 applies chain-of-thought reasoning before generating code. Rather than pattern-matching to a likely completion, it plans the implementation, identifies edge cases, and structures the output — producing code that reflects deliberate problem decomposition.
Agentic tool useThe model is designed to operate inside tool-use loops. It can call functions, interpret results, revise its approach, and continue working toward a goal across multiple turns — enabling multi-step workflows without manual re-prompting at each step.
OpenAI-compatible interfaceGrok Build 0.1 uses the standard OpenAI chat completions format. Function definitions, tool call handling, and message structure follow the same schema — no custom integration layer required for teams already using OpenAI-compatible infrastructure.
Long-context code understandingThe model can ingest entire files, module trees, and test suites in a single request. Debugging, refactoring, and feature addition tasks can be handled with full project context rather than isolated code snippets.
Core capabilities
Agentic codingPass a task description and relevant context. The model plans the implementation, writes the code, and can call tools to verify, test, or extend its output — completing multi-step development tasks end to end.
Reasoning and problem decompositionSuited for tasks that require more than code generation: architecture decisions, debugging root cause analysis, algorithm selection, and stepwise planning for complex engineering problems.
Function calling and tool integrationDefine tools in the standard format and the model will call them as needed during a task — querying databases, running tests, fetching documentation, or invoking external APIs as part of its reasoning loop.
Code review and refactoringSubmit existing code for analysis. The model identifies bugs, suggests structural improvements, rewrites for clarity or performance, and explains its reasoning — acting as a technical reviewer rather than just a generator.
Who should use Grok Build 0.1?
Agent and automation developersEngineers building coding agents, CI/CD automation, or developer tooling that requires a model capable of multi-step reasoning and autonomous task completion.
Backend and full-stack teamsTeams accelerating feature development, bug fixing, and refactoring across codebases — with a model that understands project-level context rather than isolated functions.
Technical product teamsProduct engineers who need a reliable reasoning model for structured problem-solving, API design, and implementation planning alongside code generation.
Platforms building coding assistantsIDEs, developer tools, and AI-assisted coding platforms that need a capable, OpenAI-compatible backbone for their coding workflows.
What exactly is Grok Build 0.1?
Grok Build 0.1 is xAI's reasoning and coding model built for agentic software development. It is designed to plan, write, debug, and iterate on code across multi-step tasks — operating as an autonomous coding agent rather than a single-turn code generator. The model supports function calling, tool use, and is fully OpenAI-compatible.
API Pricing
* Input: $1.30 / 1M tokens
* Output: $2.60 / 1M tokens
Architecture: what makes it capable
Reasoning-first designGrok Build 0.1 applies chain-of-thought reasoning before generating code. Rather than pattern-matching to a likely completion, it plans the implementation, identifies edge cases, and structures the output — producing code that reflects deliberate problem decomposition.
Agentic tool useThe model is designed to operate inside tool-use loops. It can call functions, interpret results, revise its approach, and continue working toward a goal across multiple turns — enabling multi-step workflows without manual re-prompting at each step.
OpenAI-compatible interfaceGrok Build 0.1 uses the standard OpenAI chat completions format. Function definitions, tool call handling, and message structure follow the same schema — no custom integration layer required for teams already using OpenAI-compatible infrastructure.
Long-context code understandingThe model can ingest entire files, module trees, and test suites in a single request. Debugging, refactoring, and feature addition tasks can be handled with full project context rather than isolated code snippets.
Core capabilities
Agentic codingPass a task description and relevant context. The model plans the implementation, writes the code, and can call tools to verify, test, or extend its output — completing multi-step development tasks end to end.
Reasoning and problem decompositionSuited for tasks that require more than code generation: architecture decisions, debugging root cause analysis, algorithm selection, and stepwise planning for complex engineering problems.
Function calling and tool integrationDefine tools in the standard format and the model will call them as needed during a task — querying databases, running tests, fetching documentation, or invoking external APIs as part of its reasoning loop.
Code review and refactoringSubmit existing code for analysis. The model identifies bugs, suggests structural improvements, rewrites for clarity or performance, and explains its reasoning — acting as a technical reviewer rather than just a generator.
Who should use Grok Build 0.1?
Agent and automation developersEngineers building coding agents, CI/CD automation, or developer tooling that requires a model capable of multi-step reasoning and autonomous task completion.
Backend and full-stack teamsTeams accelerating feature development, bug fixing, and refactoring across codebases — with a model that understands project-level context rather than isolated functions.
Technical product teamsProduct engineers who need a reliable reasoning model for structured problem-solving, API design, and implementation planning alongside code generation.
Platforms building coding assistantsIDEs, developer tools, and AI-assisted coding platforms that need a capable, OpenAI-compatible backbone for their coding workflows.
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