Last refreshed 2026-10-06. Next refresh: weekly.
Why use Mixtral 8x22B v0.1 on NVIDIA NIM?
NVIDIA NIM offers Mixtral 8x22B v0.1. NVIDIA NIM is NVIDIA's deployment platform for GPU-accelerated inference microservices.
Compare Mixtral 8x22B v0.1 across 8 providers to find the best fit for your use caseSetup recipe
Docs fallbackUse the provider REST API or SDKCreate a provider API keymodel: mistralai/mixtral-8x22b-v0.1mistralai/mixtral-8x22b-v0.1Request example
mistralai/mixtral-8x22b-v0.1.Gotchas
- Use provider model ID "mistralai/mixtral-8x22b-v0.1", not the LLMReference slug "mixtral-8x22b-v0.1".
Compare Mixtral 8x22B v0.1 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| NVIDIA NIM | — | — |
| OctoAI API (Deprecated) | — | — |
| Fireworks AI | — | — |
| DeepInfra | $0.65 | $0.65 |
| Baseten API | — | — |
Capabilities
No model capability flags are currently sourced.
About Mixtral 8x22B v0.1
The Mixtral 8x22B v0.1 is a pretrained generative Sparse Mixture of Experts (MoE) model created by Mistral AI [1][2][4]. It utilizes a specialized architecture where different sub-models, termed "experts," manage distinct input segments, enhancing both efficiency and performance relative to traditional large language models [2][10][12]. This model features an impressive 176 billion parameters and supports a context length of 65,000 tokens [10][13]. It excels in text generation, completion, and question answering, outperforming models like LLaMA 2 70B on various benchmarks [4][5][7]. Nonetheless, as a base model, it lacks inherent moderation capabilities, potentially generating inappropriate or harmful content without filtration [2][4][10].