Apply your own routing policies, reduce token costs automatically, and see every routing decision in real time with Merge Gateway.
How Grok 4.1 Fast Reasoning performs*
Intelligence - general reasoning and knowledge
39
Coding - code generation and problem-solving
31
What Grok 4.1 Fast Reasoning costs to run
| Vendor | Input / 1M tokens | Output / 1M tokens | Zero data retention |
| --- | ---: | ---: | --- |
| xAI | $0.2000 | $0.5000 | Yes |
Test Grok 4.1 Fast Reasoning
with Gateway’s Simulator
See a prompt's output, token spend, latency, and more with Grok 4.1 Fast Reasoning.
Route requests to Grok 4.1 Fast Reasoning in minutes
To get started in seconds, add our Gateway Implementation skill to your project, or pick your preferred SDK below. Check out our other quick start skills here.
Install the Merge Gateway SDK
Python
1$ pip install merge-gateway-sdkSend a request
Python
1from merge_gateway import MergeGateway
2
3client = MergeGateway(api_key="YOUR_API_KEY")
4
5response = client.responses.create(
6 model="openai/gpt-5.2",
7 input=[
8 {"type": "message", "role": "system", "content": "You are a helpful programming tutor. Explain the concepts clearly with practical examples."},
9 {"type": "message", "role": "user", "content": "Explain the concept of recursion in programming with a simple set of examples."},
10 ],
11)
12
13print(response.output[0].content[0].text)Try a diffrent model
Swap the model string to route to a different provider. No other code changes needed.
Anthropic
1response = client.responses.create(
2 model="anthropic/claude-sonnet-4-20250514",
3 input=[
4 {"type": "message", "role": "system", "content": "You are a helpful programming tutor. Explain the concepts clearly with practical examples."},
5 {"type": "message", "role": "user", "content": "Explain the concept of recursion in programming with a simple set of examples."},
6 ],
7)Point to Gateway
Python
1from openai import OpenAI
2
3client = OpenAI(
4 api_key="YOUR_API_KEY",
5 base_url="https://api-gateway.merge.dev/v1/openai",
6)Send a request
Use the standard chat.completions.create method. No provider prefix needed on the model name.
Python
1response = client.chat.completions.create(
2 model="gpt-5.2",
3 messages=[
4 {"role": "system", "content": "You are a helpful programming tutor. Explain the concepts clearly with practical examples."},
5 {"role": "user", "content": "Explain the concept of recursion in programming with a simple set of examples."},
6 ],
7)
8
9print(response.choices[0].message.content)Install packages
1npm install merge-gateway-ai-sdk-provider aiCreate the provider
TypeScript
1import { createMergeGateway } from "merge-gateway-ai-sdk-provider";
2
3const gateway = createMergeGateway({
4 apiKey: "YOUR_API_KEY",
5});Send a request
Use generateText to send a request. Model names use the provider/model format.
TypeScript
1import { generateText } from "ai";
2
3const { text } = await generateText({
4 model: gateway("openai/gpt-4o"),
5 prompt: "Explain the concept of recursion in programming with a simple set of examples.",
6});
7
8console.log(text);If you already have @ai-sdk/openai installed, point it at Gateway with a base URL change:
TypeScript
1import { createOpenAI } from "@ai-sdk/openai";
2
3const gateway = createOpenAI({
4 apiKey: "YOUR_API_KEY",
5 baseURL: "https://api-gateway.merge.dev/v1/ai-sdk",
6});
7
8// All generateText/streamText calls work unchangedInstall the Merge Gateway SDK
Anthropic SDK
1from anthropic import Anthropic
2
3client = Anthropic(
4 api_key="YOUR_API_KEY",
5 base_url="https://api-gateway.merge.dev/v1/anthropic",
6)
7
8message = client.messages.create(
9 model="claude-sonnet-4-20250514",
10 max_tokens=1024,
11 messages=[
12 {"role": "user", "content": "Explain the concept of recursion in programming with a simple set of examples."},
13 ],
14)
15
16print(message.content[0].text)Explore other models available in Merge Gateway
Grok 4.1 Fast Reasoning FAQ
If you have additional questions about Grok 4.1 Fast Reasoning, we've addressed several more below. Keep in mind that this information was written in July, 2026 and may change over time.
Heading
What other models does xAI offer?
Grok 4.1 Fast Reasoning is xAI's newest fast tier, sitting in a lineup that runs from low-cost fast models to frontier reasoning flagships. Here are some other models xAI supports:
- Grok 4.1 Fast Non-reasoning: the non-reasoning counterpart to this model, sharing the 2M-token context window and tool-calling focus but answering without extended thinking
- Grok 4 Fast Reasoning: the prior-generation fast reasoning tier with a 2M-token context window, which Grok 4.1 Fast succeeds
- Grok 4.3: the flagship reasoning model with a 1M-token context window, priced around $1.25 per 1M input and $2.50 per 1M output
- Grok 4: the base reasoning model of the Grok 4 generation with a 256K-token context window and always-on reasoning
- Grok 3: an older non-reasoning general-purpose model for instruction following and text generation
How does Grok 4.1 Fast Reasoning differ from xAI's other models?
Grok 4.1 Fast Reasoning is xAI's best tool-calling model, tuned for accurate, fast agentic work at a low price.
- Tool calling and agentic focus: xAI positions it as its strongest tool-caller, built for real-world agentic use cases such as customer support and finance, which the older Grok 4 Fast tier was not specialized for
- Context window: 2M tokens, matching the Grok 4 Fast tiers and far above Grok 4's 256K
- Pricing: approximately $0.20 per 1M input and $0.50 per 1M output, keeping it in the lowest-cost band of the Grok lineup
- Reasoning mode: uses extended thinking, unlike its non-reasoning counterpart, for multi-step agentic tasks
- Generation: the successor fast tier to Grok 4 Fast, so it should be the default fast reasoning choice unless you're pinned to the earlier version
Grok 4.1 Fast Reasoning is best for production agents that call tools and complete multi-step tasks quickly and accurately at low cost.
What models should I consider using alongside Grok 4.1 Fast Reasoning?
No single model is optimal for every task. Here are models worth pairing with Grok 4.1 Fast Reasoning depending on what your product needs:
- Claude Opus 4.8 for the hardest reasoning or coding subtasks an agent hands off, where frontier quality matters most
- Grok 4.1 Fast Non-reasoning for the fast, no-thinking steps in an agent loop like routing or simple classification
- Gemini 3.1 Pro for long-context or multimodal steps that exceed a text-and-image agentic workflow
- GPT-5.5 as a second high-quality general model for cross-provider redundancy and comparison
- Gemini 3.5 Flash for very high-volume, low-cost inference where agentic tool use isn't required
What are the challenges of using Grok 4.1 Fast Reasoning in my product?
Like any production LLM, Grok 4.1 Fast Reasoning comes with tradeoffs worth planning for:
- Provider dependency: routing agentic traffic to a single provider is fragile if xAI has an outage or changes the model
- Cost at scale: agents that loop through many tool calls compound token costs quickly, so budgeting and step limits matter even at the low per-token price
- Reasoning token overhead: extended thinking raises output tokens and latency versus the non-reasoning variant, which matters for latency-sensitive agents
- Maturing pricing and metrics: as a newer release, published pricing and third-party benchmark figures are still settling as of 07/01/2026, so confirm current rates before forecasting
- Evaluation on your tools: tool-calling quality depends on your specific tool schemas, so test against your real toolset before committing
Why should I use Merge Gateway to route LLM requests with Grok 4.1 Fast Reasoning and every other model?
Grok 4.1 Fast Reasoning through Merge Gateway comes with the control layer around the model, not just the model:
- One API, every provider: Reach Grok 4.1 Fast Reasoning and every other major LLM through one endpoint and API key, changing models by editing a string instead of your code
- Intelligent routing and automatic failover: Merge reroutes around xAI outages automatically, and routing on cost, latency, or quality can lower spend by 40 to 60% with no code edits
- Cost governance: Keep agentic traffic on budget with project caps, and attribute every tool call and request by model, project, and tag in one dashboard
- Build Your Own Router: Define "best" for your traffic with curated benchmarks or your own evals, and let the router pick per request and explain why
- Security and compliance controls: Enforce DLP, prompt injection protection, and per-project region rules before any request reaches xAI
How can I start routing requests to Grok 4.1 Fast Reasoning via Merge Gateway?
Getting Grok 4.1 Fast Reasoning running through Merge Gateway takes a few minutes:
1. Create an account and get your API key from the dashboard.
2. Install the Merge Gateway SDK: run pip install merge-gateway-sdk (Python) or npm install merge-gateway-sdk (Node). Alternatively, if you're already using the OpenAI SDK, set base_url = "https://api-gateway.merge.dev/v1/openai" and your existing code works as-is.
3. Make your first request using the provider/model format. For Grok 4.1 Fast Reasoning, the model string is xai/grok-4.1-fast-reasoning. Swap the model string to route to any other provider without changing anything else.
4. Configure a routing policy in the dashboard to set failover behavior, cost limits, and optimization strategy. Your first policy can be as simple as naming Grok 4.1 Fast Reasoning as primary with one fallback.
Full setup instructions and SDK references are in the Merge Gateway docs.
Try Grok 4.1 Fast Reasoning through Merge Gateway
Route, observe, and control AI requests across providers from one API.
