Grok-4-Fast is xAI’s new cost-efficient reasoning model designed to make high-quality reasoning and web search capabilities cheaper and faster for both consumer and developer use. xAI positions it as a frontier offering that preserves Grok-4’s benchmark performance while improving token efficiency, and ships two variants tuned for either reasoning or non-reasoning workloads.
Key features (quick list)
- Two model variants:
grok-4-fast-reasoningandgrok-4-fast-non-reasoning(tunable for depth vs. speed). - Very large context window: up to 2,000,000 tokens, enabling extremely long documents / multi-hour transcripts / multi-document workflows.
- Token efficiency / cost focus: xAI reports ~40% fewer thinking tokens on average versus Grok-4 and a claimed ~98% reduction in cost to achieve the same benchmark performance (on the metrics xAI reports).
- Native tool / browsing integration: trained end-to-end with tool-use RL for web/X browsing, code execution and agentic search behaviors.
- Multimodal & function calling: supports images and structured outputs; function calling and structured response formats are supported in the API.
Technical details
Unified reasoning architecture: Grok-4-Fast uses a single model weightbase that can be steered into reasoning (long chain-of-thought) or non-reasoning (fast replies) behavior through system prompts or variant selection, rather than shipping two entirely separate backbone models. This reduces switching latency and token cost for mixed workloads.
Reinforcement learning for intelligence density: xAI reports using large-scale reinforcement learning focused on intelligence density (maximizing performance per token), which is the basis for the stated token-efficiency gains.
Tool conditioning and agentic search: Grok-4-Fast was trained and evaluated on tasks that require invoking tools (web browsing, X search, code execution). The model is presented as adept at choosing when to call tools and how to stitch browsing evidence into answers.
Benchmark performance
Improvements in BrowseComp (44.9% pass\@1 vs 43.0% for Grok-4), SimpleQA (95.0% vs 94.0%), and large gains in certain Chinese-language browsing/search arenas. xAI also reports a top ranking in LMArena’s Search Arena for a grok-4-fast-search variant.
Model versions & naming
Public names announced by xAI: grok-4-fast-reasoning and grok-4-fast-non-reasoning. Each variant reports the same 2M token context limit. The platform also continues to host the earlier Grok-4 flagship (e.g., grok-4-0709 variants used previously).
Limitations and safety considerations
- Content-safety concerns: reporting from investigative outlets indicates xAI’s Grok family (and some Grok features) have been developed with permissive content options and that some internal workflows exposed annotators to highly disturbing material. There are explicit concerns about moderation robustness and reporting to authorities for illegal content. These safety and compliance issues are material when deploying any Grok variant in production.
- Independent verification: many of xAI’s performance/economy claims are self-reported; independent benchmarks and peer reviews are still being published. Treat cost-efficiency claims as vendor-provided until third-party replication is available.
- Operational risks: because Grok-4-Fast is framed for agentic browsing, users should note hallucination, data-freshness limits (despite browsing capability), and privacy considerations when the model is used with external tools or live web queries.
Typical & recommended use cases
- High-throughput search and retrieval — search agents that need fast multi-hop web reasoning.
- Agentic assistants & bots — agents that combine browsing, code execution, and asynchronous tool calls (where allowed).
- Cost-sensitive production deployments — services that require many calls and want improved token-to-utility economics versus a heavier base model.
- Developer experimentation — prototyping multimodal or web-augmented flows that rely on fast, repeated queries.
How to call grok-4-fast API from CometAPI
grok-code-fast-1 API Pricing in CometAPI，20% off the official price:
| grok-4-fast-non-reasoning | Input Tokens: $0.16/ M tokens Output Tokens: $0.40/ M tokens |
| grok-4-fast-reasoning | Input Tokens: $0.16/ M tokens Output Tokens: $0.40/ M tokens |
Required Steps
- Log in to cometapi.com. If you are not our user yet, please register first
- Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.
Use Method
- Select the “
grok-4-fast-reasoning” / “grok-4-fast-reasoning” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. - Replace <YOUR_API_KEY> with your actual CometAPI key from your account.
- Insert your question or request into the content field—this is what the model will respond to.
- . Process the API response to get the generated answer.
CometAPI provides a fully compatible REST API—for seamless migration. Key details to API doc:
- Base URL: https://api.cometapi.com/v1/chat/completions
- Model Names:“
grok-4-fast-reasoning” / “grok-4-fast-reasoning” - Authentication: Bearer token via
Authorization: Bearer YOUR_CometAPI_API_KEYheader - Content-Type:
application/json.
API Integration & Examples
Python snippet for a ChatCompletion call through CometAPI:
pythonimport openai
openai.api_key = "YOUR_CometAPI_API_KEY"
openai.api_base = "https://api.cometapi.com/v1/chat/completions"
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Summarize grok-4-fast's main features."}
]
response = openai.ChatCompletion.create(
model="grok-4-fast-reasoning",
messages=messages,
temperature=0.7,
max_tokens=500
)
print(response.choices[0].message['content'])See Also Grok 4
