GPT-5.3-Codex vs Mixtral 8x22B v0.1
GPT-5.3-Codex (2026) and Mixtral 8x22B v0.1 (2024) are agentic coding models from OpenAI and MistralAI. GPT-5.3-Codex ships a not-yet-sourced context window, while Mixtral 8x22B v0.1 ships a 64K-token context window. On pricing, Mixtral 8x22B v0.1 costs $0.3/1M input tokens versus $1.75/1M 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 8x22B v0.1 is ~483% cheaper at $0.3/1M; pay for GPT-5.3-Codex only for coding workflow support.
Specs
| Released | 2026-02-05 | 2024-04-17 |
| Context window | — | 64K |
| Parameters | — | 8x22B |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| GPT-5.3-Codex | Mixtral 8x22B v0.1 | |
|---|---|---|
| Input price | $1.75/1M tokens | $0.3/1M tokens |
| Output price | $14/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| GPT-5.3-Codex | Mixtral 8x22B v0.1 | |
|---|---|---|
| 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 multimodal input: GPT-5.3-Codex, function calling: GPT-5.3-Codex, tool use: GPT-5.3-Codex, structured outputs: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. 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, GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens, while Mixtral 8x22B v0.1 lists $0.3/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x22B v0.1 lower by about $4.95 per million blended tokens. Availability is 1 providers versus 8, so concentration risk also matters.
Choose GPT-5.3-Codex when coding workflow support are central to the workload. Choose Mixtral 8x22B v0.1 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 is cheaper, GPT-5.3-Codex or Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.3-Codex or Mixtral 8x22B v0.1 open source?
GPT-5.3-Codex is listed under Proprietary. Mixtral 8x22B v0.1 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 multimodal input, GPT-5.3-Codex or Mixtral 8x22B v0.1?
GPT-5.3-Codex 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 function calling, GPT-5.3-Codex or Mixtral 8x22B v0.1?
GPT-5.3-Codex 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.
Which is better for tool use, GPT-5.3-Codex or Mixtral 8x22B v0.1?
GPT-5.3-Codex has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Mixtral 8x22B v0.1?
GPT-5.3-Codex is available on OpenRouter. Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten 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.