Essential AI: Rnj 1 Instruct

Public pricingIntelligence 79/100Medium memoryTool-Nutzung

EssentialAI: Rnj 1 Instruct ist ein Text-Modell für Schlussfolgern und Problemlösen. Es verbindet tiefes Schlussfolgern und Planen, einen Kontext von 33K tokens und ein kostengünstig-Profil für zuverlässige Arbeit über reasoning, analysis, and hard problem solving.

Input

$0.15/1M

Output

$0.15/1M

Cached

$0.01/1M

Batch

$0.07/1M

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Technical specifications

Rnj 1 Instruct at a glance.

Memory

32,768

tokens

Max reply

16,384

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

Dec 2025

Training cutoff

Aug 2025

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Rnj 1 Instruct

  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Rnj 1 Instruct — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Rnj 1 Instruct costs roughly $17 per month. Input is $0.15 /1M tokens and output is $0.15 /1M tokens.
Rnj 1 Instruct has a 32,768-token context window (medium memory — a long report or a codebase file). That means you can fit about 6,144 words of input and history in a single call.
Beyond text generation, Rnj 1 Instruct supports calling functions / tools, strict JSON output. It streams replies by default.
Rnj 1 Instruct was released in December 2025, with training data cut off around August 2025.
Models in a similar class include Command R (08-2024), DeepSeek V3.1, Llama 4 Maverick. The "Similar models" section below this FAQ links into each.

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