Meta: Llama 3.3 70B Instruct

Public pricingIntelligence 76/100Medium memoryใƒ„ใƒผใƒซๅˆฉ็”จ

Meta: Llama 3.3 70B Instruct ใฏ ใƒ†ใ‚ญใ‚นใƒˆ ใƒขใƒ‡ใƒซใงใ€ๆฑŽ็”จใƒใƒฃใƒƒใƒˆใ€ๅˆ†ๆžใ€ๆฅญๅ‹™ๅˆฉ็”จ ใซๅ‘ใ„ใฆใ„ใพใ™ใ€‚ๅฎ‰ๅฎšใ—ใŸๆฑŽ็”จๆ€ง่ƒฝใ€131K tokensใฎใ‚ณใƒณใƒ†ใ‚ญใ‚นใƒˆใ€ไฝŽใ‚ณใ‚นใƒˆใฎ็‰นๆ€งใ‚’็ต„ใฟๅˆใ‚ใ›ใ€general chat, analysis, and production workloads ใงๅฎ‰ๅฎšใ—ใŸๅ‹•ไฝœใ‚’ๆ”ฏใˆใพใ™ใ€‚ๅ“่ณชใƒป้€Ÿๅบฆใƒปใ‚ณใ‚นใƒˆ ใŒ้‡่ฆใชๅ ด้ขใซๅˆใฃใฆใŠใ‚Šใ€ๅฎ‰ๅฎšใ—ใŸๅ‡บๅŠ›ใ€ๆŸ”่ปŸใชๅฐŽๅ…ฅใ€ๆ‹กๅผตๆ€งใ‚’ๆฑ‚ใ‚ใ‚‹ใƒใƒผใƒ ใซๅฎŸ็”จ็š„ใงใ™ใ€‚ ๅฎ‰ๅฎšใ—ใŸๅฟœ็ญ”ใ€้•ทใ„ๆ–‡่„ˆๅ‡ฆ็†ใ€ใใ—ใฆ่ฉฆไฝœใ‹ใ‚‰ๆœฌ็•ชใพใงๅบƒใไฝฟใˆใ‚‹ๆŸ”่ปŸใ•ใŒๅฟ…่ฆใชๅ ด้ขใงๅฝน็ซ‹ใกใพใ™ใ€‚ ๅฎ‰ๅฎšใ—ใŸๅฟœ็ญ”ใ€้•ทใ„ๆ–‡่„ˆๅ‡ฆ็†ใ€ใใ—ใฆ่ฉฆไฝœใ‹ใ‚‰ๆœฌ็•ชใพใงๅบƒใไฝฟใˆใ‚‹ๆŸ”่ปŸใ•ใŒๅฟ…่ฆใชๅ ด้ขใงๅฝน็ซ‹ใกใพใ™ใ€‚ ๅฎ‰ๅฎšใ—ใŸๅฟœ็ญ”ใ€้•ทใ„ๆ–‡่„ˆๅ‡ฆ็†ใ€ใใ—ใฆ่ฉฆไฝœใ‹ใ‚‰ๆœฌ็•ชใพใงๅบƒใไฝฟใˆใ‚‹ๆŸ”่ปŸใ•ใŒๅฟ…่ฆใชๅ ด้ขใงๅฝน็ซ‹ใกใพใ™ใ€‚

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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1,00010,00050,000250,0001M10M

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.

  • bbh

    56.56
  • chatbot_arena_elo

    1256
  • gpqa_diamond

    50.5
  • humaneval

    88.4
  • ifeval

    92.1
  • math

    77
  • mmlu

    86
  • mmlu_pro

    68.9
  • 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 โ€” pick a vision-capable model instead.

FAQ

Llama 3.3 70B Instruct โ€” the questions we see most.

Pricing, capabilities, alternatives โ€” 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 โ€” 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.

Still unsure?

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