Meta: Llama 3.3 70B Instruct

Public pricingIntelligence 76/100Medium memory도구 활용

Meta: Llama 3.3 70B Instruct은 일반 대화, 분석, 운영 환경에 맞춘 텍스트 모델입니다. 안정적인 범용 성능, 131K tokens의 컨텍스트, 저비용 특성을 결합해 general chat, analysis, and production workloads에서 안정적인 작업을 돕습니다. 특히 품질, 속도, 비용가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

Input

$0.12/1M

Output

$0.38/1M

Cached

$0.03/1M

Batch

$0.06/1M

Calculate your Llama 3.3 70B Instruct bill.

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What would Llama 3.3 70B Instruct cost you?

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Technical specifications

Llama 3.3 70B Instruct at a glance.

Memory

131,072

tokens

Max reply

131,072

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

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu

    86

  • mmlu_pro

    68.9

  • gpqa_diamond

    50.5

  • humaneval

    88.4

  • math

    77

  • ifeval

    92.1

  • chatbot_arena_elo

    1256

  • bbh

    56.56

  • scipredict

    18.19

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 70B 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

Llama 3.3 70B 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, Llama 3.3 70B Instruct costs roughly $24 per month. Input is $0.12 /1M tokens and output is $0.38 /1M tokens.
Llama 3.3 70B Instruct 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.
Beyond text generation, Llama 3.3 70B Instruct supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Llama 3.3 70B Instruct was released in December 2024, with training data cut off around December 2023.
Models in a similar class include Llama 4 Maverick, Llama 4 Scout, Llama Guard 4 12B. The "Similar models" section below this FAQ links into each.

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