OpenRouter: Elephant

Public pricingIntelligence 79/100Large memory

Elephant — это текстовой‑модель для общение, анализ и продакшн-задачи. Она сочетает низкую задержку и эффективную инференцию, контекст 262K tokens и профиль бесплатный или почти бесплатный, обеспечивая надёжную работу в задачах general chat, analysis, and production workloads.

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1,00010,00050,000250,0001M10M

Technical specifications

Elephant at a glance.

Memory

262,144

tokens

Max reply

32,768

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

—

Released

Apr 2026

Training cutoff

—

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 Elephant

  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.
  • You need tool-use / function calling for agent workflows.

Alternatives

Similar models to compare.

FAQ

Elephant — 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

Elephant has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Elephant was released in April 2026.
Models in a similar class include Auto Router, Free Models Router, Gemma 4 26B A4B. The "Similar models" section below this FAQ links into each.

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