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How much does an AI agent cost to run Proposal Drafting?

Token cost benchmark for an autonomous Proposal Drafting agent, across 24 models. Prices as of 25 Oct 2026.

An agent for Proposal Drafting on the clean path costs about $0.0210 to $2.10 per outcome depending on the model, around 27x the cost of a single chat message. At 10,000 outcomes a month that is roughly $210 to $21,020.
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Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
Claude Haiku 5.5$0.10$0.50$0.0210$210
GPT-6 Luna$0.10$0.50$0.0210$210
Llama 4 Maverick$0.25$0.87$0.0496$496
DeepSeek V4.1 Flash$0.30$1.20$0.0607$607
Gemini 2.5 Flash$0.30$2.50$0.0709$709
Mistral Large 3$0.50$1.50$0.0973$973
Gemini 3.8 Flash$0.75$3.75$0.158$1,576
Claude Haiku 4.5$1.00$5.00$0.210$2,102
DeepSeek V4 Pro$1.32$3.96$0.257$2,569
Mistral Large 4$1.36$4.18$0.265$2,654
Gemini 2.5 Pro$1.25$10.00$0.292$2,920
Grok 4.7$2.00$6.00$0.389$3,892
Claude Sonnet 5.5$2.00$10.00$0.420$4,204
Claude Sonnet 5$2.00$10.00$0.420$4,204
GPT-6.1 Sol$2.00$10.00$0.420$4,204
Gemini 4 Argon$2.00$10.00$0.420$4,204
Gemini 3.1 Pro$2.00$12.00$0.436$4,360
Claude Sonnet 4.6$3.00$15.00$0.631$6,306
Claude Opus 5.5$4.00$20.00$0.841$8,408
Claude Opus 5$5.00$25.00$1.05$10,510
Claude Opus 4.8$5.00$25.00$1.05$10,510
Claude Fable 5.1$10.00$50.00$2.10$21,020
Claude Fable 5$10.00$50.00$2.10$21,020
GPT-6 Astra$10.00$50.00$2.10$21,020

*At 10,000 outcomes per month. Cheapest model highlighted.

What this agent does

The clean-path steps this benchmark prices:

  1. Gather Requirements
  2. Enough info?
  3. Select Template
  4. Configure Products
  5. Calculate Pricing
  6. Discount > threshold?
  7. Draft Proposal
  8. Standard terms?
  9. Assemble & QA
  10. Send Proposal

What drives the cost

This path runs 10 steps: 3 tool calls, 4 reasoning steps and 3 decision points. Tool steps make two model calls each, and the agent re-reads its growing context on every call. That compounding is why one Proposal Drafting outcome costs about 27x a single chat message ($0.631 on Claude Sonnet 4.6), not the price of one message.

Why these numbers matter.

How this benchmark is calculated

These figures are modeled estimates, not metered bills. We price a generic, representative Proposal Drafting workflow across 24 models using the same cost engine as the live estimator, at each model’s published list price (checked 25 Oct 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so use these as starting points, tune the assumptions in the estimator, and validate against your real usage. Illustrative estimates, not financial advice.

Frequently asked questions

How much does an AI agent cost to run Proposal Drafting?

On the clean path with default assumptions, an agent for Proposal Drafting costs about $0.0210 to $2.10 per outcome depending on the model, or roughly $210 to $21,020 per month at 10,000 outcomes. The cheapest model here is Claude Haiku 5.5 at $0.0210; the most expensive is GPT-6 Astra at $2.10.

Why does an AI agent cost more than a single chatbot message?

An agent does not make one model call. It plans, calls tools, retrieves context and re-reads its growing working context on every step. For Proposal Drafting that adds up to about 27x the cost of a single chat message.

Which model is cheapest for Proposal Drafting?

Across the 24 models benchmarked, Claude Haiku 5.5 is cheapest at $0.0210 per outcome and GPT-6 Astra is the most expensive at $2.10. A cheaper model is not always the right choice, but it sets the floor for this workflow.

How can I reduce the cost of an agent for Proposal Drafting?

The biggest levers are prompt caching on the base context, fewer planning loops, smaller tool results, less retrieval, and choosing a cheaper model where quality allows. You can test each lever in the live estimator.

What is this Proposal Drafting benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Proposal Drafting workflow across 24 models with the same cost engine as the live estimator, at each model's published list price (checked 25 Oct 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so treat these as starting points, tune them in the estimator, and validate against your own usage.

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