Sao10K: Llama 3.3 Euryale 70B

Public pricingIntelligence 79/100Medium memory

Sao10K: Llama 3.3 Euryale 70B es un modelo texto pensado para chat general, análisis y uso en producción. Combina un rendimiento general estable, un contexto de 131K tokens y un perfil costo equilibrado para trabajar con fiabilidad en general chat, analysis, and production workloads.

Input

$0.65/1M

Output

$0.75/1M

Cached

$0.07/1M

Batch

$0.33/1M

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Technical specifications

Llama 3.3 Euryale 70B at a glance.

Memory

131,072

tokens

Max reply

16,384

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

llama3

Released

Dec 2024

Training cutoff

Dec 2023

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 Llama 3.3 Euryale 70B

  • 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

Llama 3.3 Euryale 70B — 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, Llama 3.3 Euryale 70B costs roughly $79 per month. Input is $0.65 /1M tokens and output is $0.75 /1M tokens.
Llama 3.3 Euryale 70B has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Llama 3.3 Euryale 70B was released in December 2024, with training data cut off around December 2023.
Models in a similar class include Llama 3.1 Euryale 70B v2.2, Llama 3 8B Lunaris, Llama 3 Euryale 70B v2.1. The "Similar models" section below this FAQ links into each.

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