Meta: Llama 3.3 70B Instruct
meta-llama/llama-3.3-70b-instruct
- context
- 131K
- modalities
- text → text
- capabilities
- Tool use, Structured output, Low cost
Overview
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Providers
- AkashMLView AkashML
- CloudflareView Cloudflare
- CoreWeaveView CoreWeave
- DeepInfraView DeepInfra
- GoogleView Google
- GroqView Groq
- NovitaView Novita
- ParasailView Parasail
- PrimeIntellectView PrimeIntellect
- sambanova-turbo
- TogetherView Together
Access method depends on provider and account setup.
Pricing
| provider | input / 1M | output / 1M |
|---|---|---|
| AkashML | $0.20 | $0.52 |
| Cloudflare | $0.293 | $2.253 |
| CoreWeave | $0.71 | $0.71 |
| DeepInfra | $0.10 | $0.32 |
| Googlegoogle-vertex | $0.72 | $0.72 |
| Googlegoogle-vertex/us-central1 | $0.72 | $0.72 |
| Groq | $0.59 | $0.79 |
| Novita | $0.135 | $0.40 |
| Parasail | $0.22 | $0.50 |
| PrimeIntellect | $1.04 | $2.253 |
| sambanova-turbo | $0.45 | $0.90 |
| Together | $1.04 | $1.04 |
AkashML
- input / 1M
- $0.20
- output / 1M
- $0.52
Cloudflare
- input / 1M
- $0.293
- output / 1M
- $2.253
CoreWeave
- input / 1M
- $0.71
- output / 1M
- $0.71
DeepInfra
- input / 1M
- $0.10
- output / 1M
- $0.32
Google
google-vertex
- input / 1M
- $0.72
- output / 1M
- $0.72
Google
google-vertex/us-central1
- input / 1M
- $0.72
- output / 1M
- $0.72
Groq
- input / 1M
- $0.59
- output / 1M
- $0.79
Novita
- input / 1M
- $0.135
- output / 1M
- $0.40
Parasail
- input / 1M
- $0.22
- output / 1M
- $0.50
PrimeIntellect
- input / 1M
- $1.04
- output / 1M
- $2.253
sambanova-turbo
- input / 1M
- $0.45
- output / 1M
- $0.90
Together
- input / 1M
- $1.04
- output / 1M
- $1.04
Use this model
through Nautili
Route requests to Meta: Llama 3.3 70B Instruct through your Nautili gateway using a supported SDK or the Nautili SDK.
Connect your stack to Nautili
Route across supported providers through one control layer.