What is Grok Build 0.1?
Grok Build 0.1 is a coding-specialized model provided through the SpaceXAI API. It powers Grok Build and is positioned for agentic coding: software tasks in which the model examines a problem, reasons about possible changes, uses tools, and helps carry a development workflow through several steps.
Its documented use cases include web development, debugging, software engineering, workflow automation, tool calling and integrations based on the Model Context Protocol (MCP). MCP is a standard way for an AI application to connect a model to external tools or data sources. In practical terms, that makes Grok Build 0.1 more relevant to coding agents and development assistants than to general-purpose chat or media generation.
SpaceXAI lists the model as current and in public beta. The documented release date is May 29, 2026. The canonical API model ID is grok-build-0.1.
Where it fits in the SpaceXAI lineup
Grok Build 0.1 sits in the Grok family as a model aimed specifically at coding speed and agentic development. It should not be confused with a general Grok assistant subscription or with a model that generates images, video or audio. The model is exposed through the developer API, while Grok Build is the product experience built around it.
SpaceXAI also documents aliases including grok-code-fast-1, grok-code-fast and grok-code-fast-1-0825. The former grok-code-fast-1 identifier was retired as an independent model on May 15, 2026 and routes to Grok Build 0.1. For new integrations, the canonical model ID is the clearest choice because aliases and routing can change.
Key specifications
| Specification | Grok Build 0.1 |
|---|---|
| Provider | SpaceXAI |
| Model type | Coding and agentic software-engineering model |
| Availability | Public beta through the SpaceXAI API |
| Context window | 256,000 tokens |
| Input | Text and images |
| Output | Text, including code and structured responses |
| Reasoning | Supported; editorial rating: 8/10 |
| Function and tool use | Supported |
| Structured outputs | Supported |
| Streaming | Supported through the text-generation API |
| Batch API | Not supported |
| Maximum output tokens | Not documented in the supplied model information |
The 256,000-token context window is the amount of text and other supported input the model can consider in one request. That is useful for repository excerpts, long technical specifications, issue histories and large sets of tool results. It does not mean that the model can return 256,000 tokens in its answer: SpaceXAI has not documented a maximum output-token limit in the supplied specifications.
Coding and reasoning capabilities
Grok Build 0.1 is intended to help with the full development loop rather than only autocomplete-style code generation. Suitable tasks include writing a web component, tracing a bug through several files, proposing a patch, explaining a build failure, transforming code between formats, or coordinating a sequence of tool calls.
The model supports reasoning, but the supplied research does not provide a standardized benchmark or a provider-published reasoning score. The editorial assessment rates its reasoning at 8/10 and coding at 9/10. Those are comparative editorial judgments, not measurements published by SpaceXAI, so they should be treated as guidance rather than guaranteed performance.
Function calling allows an application to define tools that the model can request, such as a code search function, test runner, issue tracker or deployment check. The application remains responsible for executing those functions and deciding which actions are safe. Structured outputs can help the model return data in an expected schema, which is useful for agent state, patch plans and tool arguments. A separate legacy JSON-mode capability is not independently confirmed, so structured outputs should not automatically be described as the same feature.
Supported modalities and unsupported workloads
The model accepts text and image input and produces text output. Image input can be useful when a coding task involves a screenshot of a user interface, an error message, a diagram or another visual reference. The supplied documentation does not identify audio or video input support for this model.
Grok Build 0.1 does not directly produce images, video, audio, music or speech. That distinction matters because the wider Grok ecosystem includes media-generation features, but those capabilities should not be assumed to belong to this API model. It is also not presented as an embedding model.
The model page states that Batch API support is unavailable. It is therefore a better fit for interactive development and agentic requests than for large, offline batches of independent prompts.
Pricing and cost trade-offs
SpaceXAI's standard pricing is:
- Input: $1.00 per 1 million tokens.
- Cached input: $0.20 per 1 million tokens.
- Output: $2.00 per 1 million tokens.
For prompts exceeding 200,000 tokens, the documented long-context rates are $2.00 per 1 million input tokens, $0.40 per 1 million cached input tokens and $4.00 per 1 million output tokens. The higher long-context rates apply to the request based on prompt length, so applications that regularly send very large repositories or histories should account for them when estimating cost.
These prices make the model attractive when response speed and coding throughput matter, especially for interactive agents that need several model calls. Caching can reduce the cost of repeatedly supplied context, such as stable system instructions, repository metadata or documentation. However, output costs are twice the standard input rate, and long-context requests are more expensive. Trimming irrelevant files, reusing cached context and sending focused tool results can therefore improve both cost and response quality.
Speed, strengths and limitations
SpaceXAI presents Grok Build 0.1 as a fast coding model. The editorial assessment also rates speed at 9/10 and cost efficiency at 8/10, but these are not provider-published benchmark results. Its practical advantage is the combination of quick coding-oriented responses, tool support and a large context window rather than a claim that it will be fastest in every workload.
Its main strengths are:
- Strong alignment with agentic coding and web-development workflows.
- A 256,000-token context window for large technical inputs.
- Text and image input for code, documentation, screenshots and diagrams.
- Function calling, structured outputs and MCP-oriented integrations.
- Streaming for applications that want to display partial responses.
- Relatively low standard token pricing, with discounted cached input.
Its limitations are equally important:
- There is no documented maximum output-token limit in the supplied material.
- It produces text only and is not a direct image, video or audio generation model.
- Batch API support is unavailable.
- Long-context prompts have higher input and output rates.
- It is in public beta, so behavior, aliases, limits and availability may change.
- Editorial scores are not a substitute for task-specific testing.
Best use cases
Grok Build 0.1 is a sensible candidate when an application needs a coding agent that can combine analysis with actions. Examples include:
- Generating or modifying front-end and back-end web code.
- Reviewing a large group of files before proposing a fix.
- Investigating test failures, compiler errors and runtime problems.
- Building an assistant that searches a repository and calls development tools.
- Turning a natural-language feature request into a structured implementation plan.
- Connecting coding workflows to MCP servers, issue trackers or internal data.
- Processing screenshots alongside written requirements during UI development.
For production agents, use function permissions, validation and human approval where actions could modify code, access sensitive data or affect deployments. The model's ability to request a tool does not by itself make the requested operation safe or correct.
When to choose this model
Choose Grok Build 0.1 when coding specialization, speed, tool calling and a large working context are more important than media output or batch processing. It is particularly suitable for interactive developer tools and agents that need to inspect substantial technical context without paying the highest rates associated with larger prompts.
Another type of model may be more appropriate when the primary task is image, video, audio or speech generation; when an embedding model is required; or when a workflow depends on a Batch API. A general-purpose frontier model may also be preferable for broad reasoning tasks that are not primarily software-related, although the supplied research does not provide a direct benchmark comparison with a named alternative.
For teams evaluating it, test representative repositories and tool workflows rather than relying only on the model's coding label. Measure patch correctness, test-pass rate, tool-call accuracy, latency, output length and total token cost. That is especially important because the model is in public beta and because no provider-published benchmark results or maximum output limit are supplied here.
Bottom line
Grok Build 0.1 is a focused API model for fast, agentic software development. Its strongest combination is a 256K context window, coding-oriented behavior, image-aware input, reasoning, structured outputs and function calling at a comparatively low standard token price. It is not a universal multimodal model: it returns text, lacks Batch API support, has higher rates for very long prompts and does not have a documented maximum output limit. Developers building interactive coding agents should consider it seriously, while teams needing media generation, embeddings, batch processing or a fully documented non-beta contract should evaluate other options.