TOP 5 MOST EXPENSIVE DEEP REASONING MODELS (JUNE 2026) 研究主题 / Topic: 深度推理模型定价逻辑与时间维度 (Deep Reasoning Pricing Logic & The Time Dimension) | 分析框架 / Framework: KAI 报价引擎 (KAI Pricing Engine)

Rank

Model Name

Vendor

Input $/MTok

Output $/MTok 特性与说明 / Description & Notes Claude Mythos 5 Anthropic

Originally exclusive to Wall Street private deployments; opened for preview in May 2026. Fable 5 is already twice the price of Opus; Mythos sits a tier above Fable. The most expensive reasoning on Earth. Claude Fable 5 Anthropic ~$30 ~$150 “Costs double Opus.” Opus 4 是

“Costs double Opus.” Opus 4 is $15/$75; Fable exactly doubles that. Free until June 22, after which official pricing applies. GPT-5.5 Pro OpenAI ~$30 ~$180 AIMultiple 原文：「$180 frontier reasoning tokens (GPT-5.5 Pro)」。目前

AIMultiple original quote: “$180 frontier reasoning tokens (GPT-5.5 Pro)”. Currently the highest pricing for reasoning outputs across all public APIs. Claude Opus 4.8 Anthropic $15 $75

Anthropic’s flagship model has long commanded premium pricing. Version 4.8 features “Faster, Honest Reasoning”. Gemini 3.5 Pro Deep Think Google $3.60 $21.60

The lowest price in this tier, yet its reasoning capacity approaches Opus-level. Exceptional cost-performance, though its absolute price remains in the top five. KAI Pricing Engine | Market Intelligence Brief 1 / 3

TWO KEY FINDINGS

FIRST: A STRUCTURAL PRICING CHASM HAS EMERGED Original quote from AIMultiple— “The price gap between $0.14 commodity tokens (DeepSeek V4-Flash) and $180 frontier reasoning tokens (GPT-5.5 Pro) is already structural and will only continue to widen.” There is a staggering 1,285x difference between them. This is no longer about a single product being cheap or expensive—these are two entirely different commodities.

SECOND: MYTHOS & FABLE PRICING LOGICS VALIDATE THE CORE THESIS Anthropic pricing Fable at double the rate of Opus is not because its “model quality” is twice as good—it is because its reasoning depth is twice as great. For identical numbers of input and output tokens, Fable traverses a much longer reasoning chain, involves more thinking steps, and consumes significantly more compute. Yet, Anthropic still has not priced based on time. It relies on a crude proxy variable—“doubling the output token price”—to indirectly cover the compute consumption of deep reasoning. This is exactly the point: the dimension of time is still embedded within token pricing, rather than being explicitly extracted.

WHAT THIS MEANS — RETURNING TO YOUR CORE THESIS

Mythos, Fable, and GPT-5.5 Pro—the pricing logic underlying these three flagship models essentially conveys the exact same message: “The longer I think, the more you pay.” However, this is currently executed via “the quantity of output tokens × a higher unit price,” rather than “reasoning time × a time premium.” KAI Pricing Engine | Market Intelligence Brief 2 / 3

THE CORE PROBLEM THE KAI PRICING ENGINE RESOLVES This is precisely the challenge that the KAI pricing engine is built to address. Imagine a day when KAI simultaneously hosts Mythos’s 15-second deep reasoning and DeepSeek’s 0.15ms lightning inference. Both might return the exact same number of tokens for a given task, yet their execution times differ by 100,000x. At that point, failing to incorporate time into the pricing function is no longer just a matter of “insufficient granularity”—it becomes a fundamental pricing error. KAI Pricing Engine | Market Intelligence Brief 3 / 3