Last refreshed 2026-05-01. Next refresh: weekly.
Why use Mixtral 8x22B v0.1 on NVIDIA NIM?
NVIDIA NIM offers Mixtral 8x22B v0.1 with competitive pricing. 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: mixtral-8x22b-v0.1mixtral-8x22b-v0.1Request example
mixtral-8x22b-v0.1.Gotchas
No curated gotchas have been sourced for this exact provider/model route yet.
Compare Mixtral 8x22B v0.1 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| NVIDIA NIM | — | — |
| OctoAI API (Deprecated) | $1.20 | $1.20 |
| Fireworks AI | $1.20 | $1.20 |
| DeepInfra | $0.65 | $0.65 |
| Baseten API | — | — |
Pricing
| Type | Rate |
|---|---|
| GPU Hour Rate | $1.00/GPU·hr |
| GPU Config | 4xH100 |
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]. The model requires significant VRAM—approximately 260GB in FP16 mode and 73GB in INT4 mode—for optimal operation [10][13] and may struggle with complex contextual understanding and current knowledge. Enhanced instruct-tuned versions, such as the Mixtral-8x22B-Instruct-v0.1, address some limitations by improving instruction adherence [3][5][6].
FAQ
What is the context window for Mixtral 8x22B v0.1 on NVIDIA NIM?
Mixtral 8x22B v0.1 supports a 64,000 token context window on NVIDIA NIM.
How does NVIDIA NIM compare to other Mixtral 8x22B v0.1 providers?
Mixtral 8x22B v0.1 is available from 8 providers. The cheapest input pricing is $0.65/1M tokens from DeepInfra.
Who created Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 was created by MistralAI as part of the Mixtral model family.
Is Mixtral 8x22B v0.1 open source?
Mixtral 8x22B v0.1 is open source under Apache 2.0 according to the seed data.