Mixtral 8x7B vs o3
Mixtral 8x7B (2023) and o3 (2025) are frontier reasoning models from MistralAI and OpenAI. Mixtral 8x7B ships a 32K-token context window, while o3 ships a 128K-token context window. On Google-Proof Q&A, o3 leads by 32.9 pts. On pricing, Mixtral 8x7B costs $0.15/1M input tokens versus $1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mixtral 8x7B is ~567% cheaper at $0.15/1M; pay for o3 only for coding workflow support.
Specs
| Released | 2023-12-11 | 2025-03-31 |
| Context window | 32K | 128K |
| Parameters | 8x7B | — |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0 | Unknown |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Mixtral 8x7B | o3 | |
|---|---|---|
| Input price | $0.15/1M tokens | $1/1M tokens |
| Output price | $0.45/1M tokens | $4/1M tokens |
| Providers |
Capabilities
| Mixtral 8x7B | o3 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Mixtral 8x7B | o3 |
|---|---|---|
| Google-Proof Q&A | 54.8 | 87.7 |
| HumanEval | 80.5 | 96.7 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Mixtral 8x7B at 54.8 and o3 at 87.7, with o3 ahead by 32.9 points; HumanEval has Mixtral 8x7B at 80.5 and o3 at 96.7, with o3 ahead by 16.2 points. The largest visible gap is 32.9 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: o3, structured outputs: o3, and code execution: o3. 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 o3 lists $1/1M input and $4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B lower by about $1.66 per million blended tokens. Availability is 18 providers versus 3, 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 o3 when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Mixtral 8x7B or o3?
o3 supports 128K 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Mixtral 8x7B or o3?
Mixtral 8x7B is cheaper on tracked token pricing. Mixtral 8x7B costs $0.15/1M input and $0.45/1M output tokens. o3 costs $1/1M input and $4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mixtral 8x7B or o3 open source?
Mixtral 8x7B is listed under Apache 2.0. o3 is listed under Unknown. 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 reasoning mode, Mixtral 8x7B or o3?
o3 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.
Which is better for structured outputs, Mixtral 8x7B or o3?
o3 has the clearer documented structured outputs signal in this comparison. If structured outputs 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 o3?
Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API. o3 is available on OpenAI API, OpenRouter, and OpenAI Batch API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.