Mixtral 8x7B vs o4-mini
Mixtral 8x7B (2023) and o4-mini (2025) are frontier reasoning models from MistralAI and OpenAI. Mixtral 8x7B ships a 32K-token context window, while o4-mini ships a not-yet-sourced context window. On pricing, Mixtral 8x7B costs $0.15/1M input tokens versus $0.5/1M 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 ~233% cheaper at $0.15/1M; pay for o4-mini only for coding workflow support.
Specs
| Released | 2023-12-11 | 2025-04-16 |
| Context window | 32K | — |
| Parameters | 8x7B | — |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0 | Proprietary |
| Knowledge cutoff | 2023-12 | 2025-08 |
Pricing and availability
| Mixtral 8x7B | o4-mini | |
|---|---|---|
| Input price | $0.15/1M tokens | $0.5/1M tokens |
| Output price | $0.45/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Mixtral 8x7B | o4-mini | |
|---|---|---|
| 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: o4-mini, multimodal input: o4-mini, reasoning mode: o4-mini, function calling: o4-mini, tool use: o4-mini, structured outputs: o4-mini, and code execution: o4-mini. 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, Mixtral 8x7B lists $0.15/1M input and $0.45/1M output tokens, while o4-mini lists $0.5/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B lower by about $0.71 per million blended tokens. Availability is 18 providers versus 4, so concentration risk also matters.
Choose Mixtral 8x7B when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose o4-mini when coding workflow support 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 is cheaper, Mixtral 8x7B or o4-mini?
Mixtral 8x7B is cheaper on tracked token pricing. Mixtral 8x7B costs $0.15/1M input and $0.45/1M output tokens. o4-mini costs $0.5/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mixtral 8x7B or o4-mini open source?
Mixtral 8x7B is listed under Apache 2.0. o4-mini is listed under Proprietary. 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, Mixtral 8x7B or o4-mini?
o4-mini 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 multimodal input, Mixtral 8x7B or o4-mini?
o4-mini has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for reasoning mode, Mixtral 8x7B or o4-mini?
o4-mini has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mixtral 8x7B and o4-mini?
Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API. o4-mini is available on OpenAI API, OpenRouter, OpenAI Batch API, and Replicate 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.