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llama-3.3-70b-instruct-turboMeta

from /1M in$0.08deepinfra inc.
context131Ktokens
providers11 region
price spread1.5x2 endpoints
endpoints
2
regions
1
api
chat
released
December 2024

capabilities 1/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

The same weights cost 1.5x more on deepinfra inc. than on deepinfra inc.. That is what the endpoints table is for.

endpoints

2 / 1 region
Providers serving llama-3.3-70b-instruct-turbo, with pricing and measured performance. Best value in each column is coloured.
#flags
1DeepInfra Inc.Global131K$0.08$0.26-zdr
2DeepInfra Inc.Global131K$0.12$0.30$0.12zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Sep 12

no measured traffic for this model yet. the endpoints table above carries provider pricing

benchmarks

artificial analysis

no published benchmark scores for this model

call it

model=
deepinfra/meta-llama/Llama-3.3-70B-Instruct-Turbo:flex

this model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible
main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="deepinfra/meta-llama/Llama-3.3-70B-Instruct-Turbo:flex",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

A lightweight and ultra-fast variant of Llama 3.3 70B, for use when quick response times are needed most.

questions 5

Which providers serve llama-3.3-70b-instruct-turbo?
llama-3.3-70b-instruct-turbo is available from 1 provider through Requesty: DeepInfra Inc.. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does llama-3.3-70b-instruct-turbo cost?
Pricing starts at $0.08 per million input tokens and $0.26 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is llama-3.3-70b-instruct-turbo open weights?
Yes. llama-3.3-70b-instruct-turbo is an open-weights model from Meta, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of llama-3.3-70b-instruct-turbo?
llama-3.3-70b-instruct-turbo supports up to 131K tokens of context. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use llama-3.3-70b-instruct-turbo with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/meta-llama/Llama-3.3-70B-Instruct-Turbo:flex" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

more from meta 6

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llama-3.3-70b-instruct131K$0.133
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llama-3.1-8b-instruct16K$0.051
meta-llama-3.1-405b-instruct131K$0.801

route llama-3.3-70b-instruct-turbo through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

llama-3.3-70b-instruct-turbo1 provider2 endpointsfrom $0.08 /1M inctx 131Kspread 1.5xupdated Sep 12