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.

inclusionAI: Ling 3.1 Flash vs Reka Flash 3

A side-by-side comparison of inclusionAI: Ling 3.1 Flash ($0.16 / 1M tokens) and Reka Flash 3 ($0.35 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	inclusionAI: Ling 3.1 Flash	Reka Flash 3
Provider	inclusionAI	Reka AI
Input	$0.16 / 1M tokens	$0.35 / 1M tokens
Output	$0.47 / 1M tokens	$0.70 / 1M tokens
Cache read	$0.03 / 1M tokens	-
Context window	1,000,000	65,536
Max output	262,144	58,982
Input	text	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Oct 2, 2026	Mar 12, 2025

Key differences

inclusionAI: Ling 3.1 Flash is 55% cheaper on input tokens.
inclusionAI: Ling 3.1 Flash is 32% cheaper on output tokens.
inclusionAI: Ling 3.1 Flash reads 15.3× more context (1,000,000 tokens).
Only inclusionAI: Ling 3.1 Flash supports tool calling.
A request with 1,000 input and 500 output tokens costs $0.000394 with inclusionAI: Ling 3.1 Flash and $0.000700 with Reka Flash 3.

In depth

inclusionAI: Ling 3.1 Flash is a text model from inclusionAI, released on 2026-10-02. Reka Flash 3 is a text model from Reka AI, released on 2025-03-12. Both are served through api14 as chat models with text input and text output, so neither one handles images, audio or other non-text modalities. The main structural difference between them is scale: Ling 3.1 Flash has a context window of 1,000,000 tokens, while Reka Flash 3 has a context window of 65,536 tokens.

That gap in context length is the clearest capability difference. Ling 3.1 Flash can hold roughly fifteen times more text in a single request, which matters for long documents, large codebases, extended transcripts or multi-step agent runs where you want to keep the whole history in one call. Reka Flash 3 is built around shorter inputs. On parameters, Ling 3.1 Flash supports a wider set, including tools and tool_choice, logit_bias, min_p and repetition_penalty, none of which appear in the Reka Flash 3 list. Both models support reasoning and include_reasoning, structured_outputs, response_format on the Ling side, temperature, top_p, top_k, seed, stop, logprobs and top_logprobs, so basic sampling and structured generation are available on either. Tool calling is the practical dividing line: only Ling 3.1 Flash lists tools and tool_choice, so if your application needs function calling, that is the model to use.

For day to day work, pick based on the shape of the request rather than raw quality claims. If you are summarizing a long contract, searching across a large repository, or running an agent that accumulates context over many turns, Ling 3.1 Flash is the natural choice because the 1,000,000 token window keeps everything in one prompt and its tool support fits agent loops. If your prompts are short, such as classification, extraction, rewriting a paragraph, or a single-turn question with a modest amount of reference text, Reka Flash 3 is a reasonable fit and its output pricing is the cheaper of the two. On input pricing Ling 3.1 Flash is the cheaper side, so workloads that are input heavy and fit within 65,536 tokens can still lean toward Ling 3.1 Flash on cost, while output heavy workloads favor Reka Flash 3. Check the live price table on this page for the actual numbers before you commit.

Calling either model through api14 works the same way because the API is OpenAI compatible. You point your client at the api14 base URL, send a standard chat completions request with your messages array, and set the model field. The only change between the two is that string: use inclusionai/ling-3.1-flash for Ling 3.1 Flash and rekaai/reka-flash-3 for Reka Flash 3. Your existing OpenAI SDK code, request shape and response parsing stay as they are, so switching is a one line edit and you can route different requests to different models from the same codebase.

There are still cases where Reka Flash 3 is the better pick. If your task is output heavy and short input, its cheaper output pricing makes it the more economical option, and its parameter set covers the common sampling and structured output controls most applications need. It also has the earlier release date, so teams that already have prompts and evaluations tuned against it can keep using it without reworking anything. Ling 3.1 Flash remains the choice when you need the larger context window or tool calling, but for compact, output driven requests Reka Flash 3 holds its own.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "inclusionai/ling-3.1-flash" to "rekaai/reka-flash-3" and prompts, streaming and tools keep working.

inclusionAI: Ling 3.1 Flash details & playground →Reka Flash 3 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.chat.completions.create({
  "model": "rekaai/reka-flash-3",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

Ling 3.1 Flash vs Reka Flash 3: API price, context & features · api14