DeepSeek V3.2 vs GPT-4.1:
The 85% Savings Gap
For long-running AI agents, context accumulation is the silent killer. See how DeepSeek V3.2's aggressive pricing and native caching outperform OpenAI's latest GPT-4.1.
Input Price
GPT-4.1: $2.00 / 1M
DeepSeek V3.2: $0.28 / 1M
Context Caching
DeepSeek V3.2 offers $0.028/1M caching, making complex Browser-Use agents sustainable.
Agent ROI
Run 10x more experiments with the same budget using ClawKit presets.
Interactive Burn-Rate Simulator
Higher cache rate = Lower costs for supported models.
Why DeepSeek V3.2 is the "Agent Model" of Choice
OpenClaw and other agent frameworks rely on repeated context. Every time your agent takes a step (clicks a button, reads a screen), the entire history is sent back to the LLM. With GPT-4.1, your costs grow linearly with history length, leading to "bankruptcy steps" where a single interaction costs over $1.00.
DeepSeek V3.2 solves this through native context caching, which ClawKit enables by default in our config wizard.
Ready to switch?
Our Config Wizard has built-in presets for DeepSeek. Stop editing YAML manually and fix your environment in seconds.
Open Config WizardDeepSeek V4 Is Coming
DeepSeek V4 is expected to drop input pricing to an estimated $0.10/1M tokens — a 95% savings vs GPT-4.1. Combined with a 1M token context window, the cost gap widens even further for agent workloads.
Read the full V4 analysisFAQ: DeepSeek V3.2 vs GPT-4.1 for Agents
Is DeepSeek V3.2 as smart as GPT-4.1?
For coding and agentic reasoning (Tool Use), DeepSeek V3.2 is comparable to GPT-4.1, often exceeding it in specific logic benchmarks while costing a fraction of the price.
Does ClawKit support local DeepSeek via Ollama?
Yes. ClawKit's Config Wizard supports both DeepSeek API and local Ollama deployments, ensuring you can scale privately and cheaply.