Nace.AI: Drex Max vs TypeSafe: Jev 1.14
A side-by-side comparison of Nace.AI: Drex Max ($0.21 / 1M tokens) and TypeSafe: Jev 1.14 ($0.15 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Nace.AI: Drex Max | TypeSafe: Jev 1.14 | |
|---|---|---|
| Provider | Nace.AI | TypeSafe |
| Input | $0.21 / 1M tokens | $0.15 / 1M tokens |
| Cache read | $0.21 / 1M tokens | - |
| Context window | 262,144 | 262,144 |
| Max output | 235,929 | 235,929 |
| Input | text, image | text, image |
| Output | decisions | decisions |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Oct 21, 2026 | Oct 14, 2026 |
Key differences
- TypeSafe: Jev 1.14 is 30% cheaper on input tokens.
- A request with 1,000 input and 500 output tokens costs $0.000210 with Nace.AI: Drex Max and $0.000147 with TypeSafe: Jev 1.14.
In depth
Nace.AI: Drex Max is a model from Nace.AI, and TypeSafe: Jev 1.14 comes from TypeSafe. Both are built for decision tasks, which is the category the provider assigns to them, and both were released in October 2026, with Jev 1.14 arriving a week before Drex Max. If you are already routing work through a stack that expects a decision model rather than a chat model, these two sit in the same slot, and the choice between them comes down to the few concrete differences described below rather than to a different class of tool.
On the measured axes the two are almost identical. Both accept text and image input and both produce decisions as output, so neither gives you a modality the other lacks. Both expose a context window of 262144 tokens, which is the same figure, so long documents, large screenshots or extended conversation histories fit equally well on either side. Neither lists any supported parameters, and there is no tool-only, structured-output-only or reasoning-only capability recorded for either model, so the plumbing you write for one will look much the same for the other. The one real separation is price on input: Jev 1.14 is the cheaper of the two for input tokens. Output pricing is not meaningfully different between them.
Practically, that input price difference is the main lever when the two look otherwise equivalent. If your pipeline sends large volumes of text or many images into the model and you care about cost per call, Jev 1.14 is the leaner option on the input side. If your workload is dominated by output tokens, or by a mix where input volume is modest, the price gap narrows to something close to a tie and you can decide on other grounds, such as which provider's behaviour you have already validated for your decision task. Because output pricing is not clearly cheaper on either side, there is no strong reason to pick Drex Max on cost alone.
Calling either model through api14 works the same way, since the gateway exposes an OpenAI-compatible API. You point your client at the api14 base URL, send your request in the usual chat completions shape, and set the model field. Swap "nace-ai/drex-max" for "typesafe/jev-1.14", or the reverse, and nothing else in the request body has to change for the features both models share. Your authentication, headers, image payloads and prompt construction stay put, which makes A/B testing between the two a matter of a single string rather than a rewrite.
There is a case for Drex Max even though Jev 1.14 is cheaper on input: if you have already tuned prompts or evaluation harnesses against Drex Max and they behave as you expect, moving to save on input tokens may not be worth the revalidation effort, especially when output cost and capabilities are otherwise about equal. Similarly, if you prefer the Nace.AI provider for operational reasons you have not recorded here, staying on "nace-ai/drex-max" keeps that relationship intact. Otherwise, for input-heavy decision workloads, "typesafe/jev-1.14" is the more economical default.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "nace-ai/drex-max" to "typesafe/jev-1.14" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.post("/decisions", { body: {
"model": "typesafe/jev-1.14",
"state": "Customer: I was charged twice for my order and want my money back.",
"questions": {
"team": {
"type": "choice",
"instructions": "Which team should handle this message?",
"criteria": {
"billing": "Payments, refunds, invoices",
"support": "Product questions and bugs",
"sales": "Pricing and new purchases"
}
},
"urgent": {
"type": "noul",
"instructions": "Does this need a reply today?",
"criteria": {
"true": "Money, outage or legal risk",
"false": "Can wait"
}
}
}
} });
console.log(result.answers);
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