We use cookies. Cookies and browser storage keep you signed in and remember your preferences. With your permission we also measure how the site is used. You can any time. See our cookie policy.

New here? See how it works A 1-minute tour of the playground, models and your API key.

Respan: Span-02 vs TypeSafe: Jev 1.14

A side-by-side comparison of Respan: Span-02 ($0.04 / 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

	Respan: Span-02	TypeSafe: Jev 1.14
Provider	Respan	TypeSafe
Input	$0.04 / 1M tokens	$0.15 / 1M tokens
Context window	131,072	262,144
Max output	117,964	235,929
Input	text, image	text, image
Output	decisions	decisions
Tool calling
Structured output
Reasoning control
Added	Oct 16, 2026	Oct 14, 2026

Key differences

Respan: Span-02 is 76% cheaper on input tokens.
TypeSafe: Jev 1.14 reads 2.0× more context (262,144 tokens).
A request with 1,000 input and 500 output tokens costs $0.000035 with Respan: Span-02 and $0.000147 with TypeSafe: Jev 1.14.

In depth

Respan: Span-02 is a model from Respan, and TypeSafe: Jev 1.14 is a model from TypeSafe. Both sit in the decisions category, meaning their output is not free form prose but a decision, and both were released within days of each other in October 2026, with Jev 1.14 arriving first and Span-02 following two days later. If you are choosing between them, you are choosing between two providers that are targeting the same kind of workload rather than two fundamentally different tools.

The most concrete difference is context. Jev 1.14 accepts up to 262144 tokens, twice the 131072 tokens that Span-02 accepts, so if your prompt includes long documents, large code trees or extended conversation history, Jev 1.14 gives you considerably more room before you have to trim anything. On input modalities they match: both take text and images, and both return decisions as their only output type. Neither model lists any supported parameters, so you should not expect to tune sampling behaviour or similar knobs through the API for either one. The qualitative comparison shows no model that is alone in offering tools, structured output or reasoning, so there is no capability here that one has and the other lacks. On price, Span-02 is the cheaper of the two for input, while output pricing is not meaningfully different between them.

For practical selection, start with the context requirement. If your task fits comfortably inside 131072 tokens and input cost matters to you, Span-02 is the sensible default, since it is the cheaper input option and handles the same text and image inputs. If you routinely work near or beyond that limit, or you would rather not spend engineering time chunking and summarising inputs, Jev 1.14 is the better fit because its larger window removes that constraint. Because both emit decisions and neither exposes extra parameters, the decision logic in your application does not need to change shape between them; only the volume of context you can pass differs, along with the input price.

Calling either model through api14 works the same way, because the API is OpenAI compatible. You point your existing OpenAI client at api14, keep your usual request structure, and set the model field to respan/span-02 or typesafe/jev-1.14. Switching between them is a one line change to that model id, with no other edits to your request format, your message array or your handling of the response. That makes it cheap to test both against your own traffic rather than committing on paper.

There is one case where the cheaper model is still the right pick even though the other is larger. If your inputs are short, for example single images with a brief instruction, or short text snippets where you need a decision, the extra context of Jev 1.14 buys you nothing, and Span-02's lower input price makes it the more economical choice for that workload.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "respan/span-02" to "typesafe/jev-1.14" and prompts, streaming and tools keep working.

Respan: Span-02 details & playground →TypeSafe: Jev 1.14 details & playground →

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);

More comparisons

Span-02 vs Jev 1.14: API price, context & features · api14