Mistral Large vs Mixtral 8x7B
Mistral Large (2024) and Mixtral 8x7B (2023) are compact production models from MistralAI. Mistral Large ships a 32k-token context window, while Mixtral 8x7B ships a 32K-token context window. On pricing, Mixtral 8x7B costs $0.15/1M input tokens versus $0.32/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Mixtral 8x7B is ~113% cheaper at $0.15/1M; pay for Mistral Large only for vision-heavy evaluation.
Specs
| Released | 2024-02-08 | 2023-12-11 |
| Context window | 32k | 32K |
| Parameters | — | 8x7B |
| Architecture | - | mixture of experts |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2024-03 | 2023-12 |
Pricing and availability
| Mistral Large | Mixtral 8x7B | |
|---|---|---|
| Input price | $0.32/1M tokens | $0.15/1M tokens |
| Output price | $0.96/1M tokens | $0.45/1M tokens |
| Providers |
Capabilities
| Mistral Large | Mixtral 8x7B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Mistral Large, function calling: Mistral Large, tool use: Mistral Large, and structured outputs: Mistral Large. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Mistral Large lists $0.32/1M input and $0.96/1M output tokens, while Mixtral 8x7B lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B lower by about $0.27 per million blended tokens. Availability is 8 providers versus 18, so concentration risk also matters.
Choose Mistral Large when vision-heavy evaluation are central to the workload. Choose Mixtral 8x7B when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Mistral Large or Mixtral 8x7B?
Mistral Large supports 32k tokens, while Mixtral 8x7B supports 32K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mistral Large or Mixtral 8x7B?
Mixtral 8x7B is cheaper on tracked token pricing. Mistral Large costs $0.32/1M input and $0.96/1M output tokens. Mixtral 8x7B costs $0.15/1M input and $0.45/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large or Mixtral 8x7B open source?
Mistral Large is listed under Proprietary. Mixtral 8x7B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Mistral Large or Mixtral 8x7B?
Mistral Large has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, Mistral Large or Mixtral 8x7B?
Mistral Large has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mistral Large and Mixtral 8x7B?
Mistral Large is available on NVIDIA NIM, Microsoft Foundry, AWS Bedrock, Mistral AI Studio, and IBM watsonx. Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.