AI model comparison

Llama 3.1 405B vs Llama-3.3-70B-Instruct

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

Llama 3.1 405B and Llama-3.3-70B-Instruct both come up when teams are choosing a model for production work, and the honest answer usually depends on your workload rather than a leaderboard. This page puts their published specifications side by side — context window, token pricing, supported inputs and outputs — so you can see where they actually differ.

Side-by-sideReviewed by our team

Meta

Llama 3.1 405B

Meta's largest open-weights model, competitive with frontier closed models.

Context
128K
Max output
4.1K
Input / 1M
$3.50
Output / 1M
$3.50
Output speed
30 t/s

Accepts

  • Text input

Produces

  • Text output
VS

Meta

Llama-3.3-70B-Instruct

Popular open Llama workhorse for multilingual chat, coding, and self-hosting

Context
128K
Max output
4.1K
Input / 1M
$1.25
Output / 1M
$1.25
Output speed

Accepts

  • Text input

Produces

  • Text output

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Llama 3.1 405B leads in recorded data

No complete recorded factor currently favors this model. That does not establish lower real-world quality.

Where Llama-3.3-70B-Instruct leads in recorded data

  • Input price: $1.25
  • Output price: $1.25

Context capacity

Higher listed limit

Llama 3.1 405B:128K

Llama-3.3-70B-Instruct:128K

Same recorded value

Maximum output

Higher listed limit

Llama 3.1 405B:4.1K

Llama-3.3-70B-Instruct:4.1K

Same recorded value

Input price

Lower recorded price

Llama 3.1 405B:$3.50

Llama-3.3-70B-Instruct:$1.25

Llama-3.3-70B-Instruct

Output price

Lower recorded price

Llama 3.1 405B:$3.50

Llama-3.3-70B-Instruct:$1.25

Llama-3.3-70B-Instruct

Output speed

Higher recorded throughput

Llama 3.1 405B:30 t/s

Llama-3.3-70B-Instruct:

No complete comparison

Time to first token

Lower recorded latency

Llama 3.1 405B:0.70s

Llama-3.3-70B-Instruct:

No complete comparison

Intelligence Index

Higher directory index

Llama 3.1 405B:74.0

Llama-3.3-70B-Instruct:

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationLlama 3.1 405BLlama-3.3-70B-Instruct
ProviderMetaMeta
Model familyLlama 3.1llama
Accepted inputstexttext
Produced outputstexttext
Context window128K128K
Max output4.1K4.1K
Intelligence Index74.0
Input price / 1M$3.50$1.25Recorded lead
Output price / 1M$3.50$1.25Recorded lead
Output speed30 t/s
Time to first token0.70s
Reasoning modeNot documentedNot documented
Tool callingDocumentedDocumented
Image inputNot documentedNot documented
Audio inputNot documentedNot documented
Structured outputDocumentedNot documented
LicenseOpen weightsOpen weights
ReleasedJul 23, 2024Dec 6, 2024

Workload guidance

Which model should you choose?

On the published numbers, Llama-3.3-70B-Instruct accepts the larger context window and Llama-3.3-70B-Instruct is cheaper per input token. Which matters more depends on whether your bottleneck is document size or spend — the table above has the exact figures.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

Compare a different pair

Choose any two approved model records and review them with the same evidence rules.

Open model comparison