Context
131K
Max output
131K
Serving providers
5
Cheapest input
$0.12 /1M
Prices are on-demand list rates. Enterprise commitments (committed-use discounts, provisioned throughput, negotiated rates) can be materially lower.

Pricing by serving provider

standard tier · per 1M tokens · click a provider to expand

Input pricing runs from $0.12 to $2.68 per 1M tokens across 5 providers, so the dearest route costs 2133% more than the cheapest for the same model.

Serving providerInput /1MOutput /1MEndpoints
HyperbolicCheapest$0.12$0.301
ComponentUnitStandardBatchCached
Text input/1M tok$0.1200
Text output/1M tok$0.3000
Nebius$0.13$0.401
DeepInfra$0.40$0.401
Friendliai$0.60$0.601
Azure$2.68$3.541

Price history

input + output $/1M since we started tracking
Input Output
Input down 96% since first tracked
$0.000$1.00$2.00$3.00$4.00Oct 23Jul 21Oct 4Jun 22$0.300$0.120

Cost calculator

estimate your monthly spend on this model
$48
estimated / month

Model IDs

copy the exact identifier for your platform
hyperbolic/meta-llama/Meta-Llama-3.1-70B-Instructnebius/meta-llama/Meta-Llama-3.1-70B-Instructdeepinfra/meta-llama/Meta-Llama-3.1-70B-Instructfriendliai/meta-llama-3.1-70b-instructazure_ai/Meta-Llama-3.1-70B-Instruct

Frequently asked questions

Meta Llama 3.1 70B Instruct pricing, context and availability

How much does Meta Llama 3.1 70B Instruct cost?

Meta Llama 3.1 70B Instruct costs $0.12 per 1M input tokens and $0.30 per 1M output tokens at its cheapest provider via Hyperbolic. Across 5 serving providers, input prices range from $0.12 to $2.68 per 1M tokens.

What is the context window of Meta Llama 3.1 70B Instruct?

Meta Llama 3.1 70B Instruct accepts up to 131K tokens of context and can return up to 131K output tokens.

Which providers serve Meta Llama 3.1 70B Instruct?

Meta Llama 3.1 70B Instruct is available from 5 serving providers, each with its own pricing and model ID. Hyperbolic is currently the cheapest.

What can Meta Llama 3.1 70B Instruct do?

Meta Llama 3.1 70B Instruct supports tool use and structured output.

Other Meta models

compare pricing across the Meta lineup
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