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Mixtral 8x22B Instruct v0.3 vs o3

Mixtral 8x22B Instruct v0.3 (2024) and o3 (2025) are frontier reasoning models from MistralAI and OpenAI. Mixtral 8x22B Instruct v0.3 ships a 64K-token context window, while o3 ships a 128K-token context window. On pricing, o3 costs $1/1M input tokens versus $2/1M 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.

o3 is ~100% cheaper at $1/1M; pay for Mixtral 8x22B Instruct v0.3 only for provider fit.

Specs

Released2024-07-012025-03-31
Context window64K128K
Parameters8x22B
Architecturemixture of expertsdecoder only
LicenseApache 2.0Unknown
Knowledge cutoff--

Pricing and availability

Mixtral 8x22B Instruct v0.3o3
Input price$2/1M tokens$1/1M tokens
Output price$2/1M tokens$4/1M tokens
Providers

Capabilities

Mixtral 8x22B Instruct v0.3o3
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 reasoning mode: o3, function calling: Mixtral 8x22B Instruct v0.3, 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 8x22B Instruct v0.3 lists $2/1M input and $2/1M 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 o3 lower by about $0.1 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.

Choose Mixtral 8x22B Instruct v0.3 when provider fit are central to the workload. Choose o3 when coding workflow support, larger context windows, and lower input-token cost 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, Mixtral 8x22B Instruct v0.3 or o3?

o3 supports 128K tokens, while Mixtral 8x22B Instruct v0.3 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Mixtral 8x22B Instruct v0.3 or o3?

o3 is cheaper on tracked token pricing. Mixtral 8x22B Instruct v0.3 costs $2/1M input and $2/1M 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 8x22B Instruct v0.3 or o3 open source?

Mixtral 8x22B Instruct v0.3 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 8x22B Instruct v0.3 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 function calling, Mixtral 8x22B Instruct v0.3 or o3?

Mixtral 8x22B Instruct v0.3 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 Mixtral 8x22B Instruct v0.3 and o3?

Mixtral 8x22B Instruct v0.3 is available on Replicate 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.