GROK 4.1 FAST
2M-token context. Vision. Native X / web / news search. $0.20/$0.50 per million tokens. The pick for high-volume agentic flows where price matters and reasoning still counts.
Grok 4.1 Fast is xAI's value workhorse: 2M-token context, vision input, native X / web / news search, and prices that round to nothing. At $0.20 per million input tokens and $0.50 per million output, it's roughly 1/25th the cost of GPT-5.5 and 1/150th the cost of Claude Opus 4.7 — yet reasoning quality is strong enough for most production work. The case for Grok 4.1 Fast: high-volume agentic loops where token economics dominate, tool-calling pipelines that fan out many calls per request, classification and summarization at scale, and any workflow where you'd otherwise reach for GPT-5.4-Nano or DeepSeek V4 Flash. The case against: when you need top-of-the-stack reasoning on a single hard prompt — Grok 4.3, GPT-5.5, or Opus 4.7 will give you a cleaner answer. Think of Grok 4.1 Fast as the Honda Civic of the frontier set: not the fanciest, but the one you actually use every day.
On most benchmarks it lands a tier below Grok 4.3 / GPT-5.5 but well above older mid-tier models. For routine work — classification, summarization, agent steps — the gap to flagships is usually invisible.
$0.20 per million input tokens and $0.50 per million output tokens. Council AI bundles it inside every plan's monthly budget.
Similar price band, but Grok 4.1 Fast has a much bigger context window (2M vs 256K) and native X/web search. Pick GPT-5.4-Mini if you specifically need OpenAI's tool-calling reliability; pick Grok 4.1 Fast if you want long context and fresh web data.
For high-volume or cost-sensitive workloads, yes. For one-shot 'this needs to be right' questions, escalate to Grok 4.3 or a frontier flagship.
Yes — text and image input. Useful for screenshot triage, chart reading, and diagram interpretation at low cost.
It's real in production. Recall holds well; multi-hop reasoning across the full window does degrade past ~1M tokens as with any long-context model.