meta-llama-3.1-8b-instruct-turbo
Meta/Open weights/1 provider
A lightweight and ultra-fast variant of Llama 3.3 70B, for use when quick response times are needed most.
Which id to call
deepinfra/meta-llama/Meta-Llama-3.1-8B-Instruct-TurboThis model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
From /1M input
$0.02
DeepInfra Inc.
Context
131K
tokens
Endpoints
1
1 region
Regions
1
chat
Capabilities 1/8
1 endpoint / 1 region
Providers serving meta-llama-3.1-8b-instruct-turbo
Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.
| Rank | Privacy | ||||||
|---|---|---|---|---|---|---|---|
| 1 |  DeepInfra Inc. | Global | 131K | $0.02 | $0.05 | $0.02 | zdr |
A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
deepinfra/meta-llama/Meta-Llama-3.1-8B-Instruct-TurboThis model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from 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/Meta-Llama-3.1-8B-Instruct-Turbo", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
6
More from Meta
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llama-4-maverick-17b-128e-instruct
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llama-3.3-70b-instruct
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llama-3.3-70b-instruct-turbo
131K ctx/from $0.08/1 provider
llama-3.2-90b-vision-instruct
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llama-3.1-8b-instruct
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Reference
meta-llama-3.1-8b-instruct-turbo questions
Which providers serve meta-llama-3.1-8b-instruct-turbo?
meta-llama-3.1-8b-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 meta-llama-3.1-8b-instruct-turbo cost?
Pricing starts at $0.02 per million input tokens and $0.05 per million output tokens on DeepInfra Inc., the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
Is meta-llama-3.1-8b-instruct-turbo open weights?
Yes. meta-llama-3.1-8b-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 meta-llama-3.1-8b-instruct-turbo?
meta-llama-3.1-8b-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 meta-llama-3.1-8b-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/Meta-Llama-3.1-8B-Instruct-Turbo" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Route meta-llama-3.1-8b-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.