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DeepSeek V4.1 Flash now available on AI Gateway

DeepSeek V4.1 Flash brings vision, tool use, reasoning, and prompt caching to Vercel AI Gateway, with direct setup paths for Claude Code, Codex, and Cursor.

Vercel · Sep 9, 2026
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Source Summary

**DeepSeek V4.1 Flash** is available through Vercel AI Gateway with mixed text-and-image input, reasoning, tool use, and prompt caching. It has a **1 million-token context window** and supports outputs up to **384,000 tokens**.

Practical Implication

Builders can select deepseek/deepseek-v4.1-flash after running the latest Vercel CLI setup, then test screenshot reading or chart extraction inside Claude Code, Codex, or Cursor. Gateway controls cover usage, cost, retries, failover, budgets, and routing.

Agent-Ready Context
**DeepSeek V4.1 Flash** is available through Vercel AI Gateway with mixed text-and-image input, reasoning, tool use, and prompt caching. It has a **1 million-token context window** and supports outputs up to **384,000 tokens**.

Builders can select deepseek/deepseek-v4.1-flash after running the latest Vercel CLI setup, then test screenshot reading or chart extraction inside Claude Code, Codex, or Cursor. Gateway controls cover usage, cost, retries, failover, budgets, and routing.

The material gives architecture and capacity claims but no coding-agent benchmarks, latency measurements, or workload-specific quality results. Large stated limits do not establish reliable performance at those limits.
Connected Context · Feed7 Judgment

This expands the gateway’s multimodal coding-agent pool with unusually large stated context and output limits, prompt caching, and existing routing controls. It strengthens the case for testing consolidated screenshot, chart, and code workflows through one client, but does not distinguish DeepSeek on quality, latency, reliability, or cost; capacity claims remain evaluation inputs, not routing evidence.

Context Map
infracodingimage#gateways#model-selection#coding-agents
Uncertainty
The material gives architecture and capacity claims but no coding-agent benchmarks, latency measurements, or workload-specific quality results. Large stated limits do not establish reliable performance at those limits.