Claude Opus 4.5 vs Mixtral 8x7B
Claude Opus 4.5 (2025) and Mixtral 8x7B (2023) are frontier reasoning models from Anthropic and MistralAI. Claude Opus 4.5 ships a 200K-token context window, while Mixtral 8x7B ships a 32K-token context window. On pricing, Mixtral 8x7B costs $0.15/1M input tokens versus $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 ~3233% cheaper at $0.15/1M; pay for Claude Opus 4.5 only for coding workflow support.
Specs
| Released | 2025-11-01 | 2023-12-11 |
| Context window | 200K | 32K |
| Parameters | — | 8x7B |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2025-12 | 2023-12 |
Pricing and availability
| Claude Opus 4.5 | Mixtral 8x7B | |
|---|---|---|
| Input price | $5/1M tokens | $0.15/1M tokens |
| Output price | $25/1M tokens | $0.45/1M tokens |
| Providers |
Capabilities
| Claude Opus 4.5 | 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: Claude Opus 4.5, multimodal input: Claude Opus 4.5, reasoning mode: Claude Opus 4.5, function calling: Claude Opus 4.5, tool use: Claude Opus 4.5, structured outputs: Claude Opus 4.5, and code execution: Claude Opus 4.5. 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, Claude Opus 4.5 lists $5/1M input and $25/1M 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 $10.76 per million blended tokens. Availability is 6 providers versus 18, so concentration risk also matters.
Choose Claude Opus 4.5 when coding workflow support and larger context windows 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.
FAQ
Which has a larger context window, Claude Opus 4.5 or Mixtral 8x7B?
Claude Opus 4.5 supports 200K 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, Claude Opus 4.5 or Mixtral 8x7B?
Mixtral 8x7B is cheaper on tracked token pricing. Claude Opus 4.5 costs $5/1M input and $25/1M 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 Claude Opus 4.5 or Mixtral 8x7B open source?
Claude Opus 4.5 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, Claude Opus 4.5 or Mixtral 8x7B?
Claude Opus 4.5 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.
Which is better for multimodal input, Claude Opus 4.5 or Mixtral 8x7B?
Claude Opus 4.5 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.
Where can I run Claude Opus 4.5 and Mixtral 8x7B?
Claude Opus 4.5 is available on Microsoft Foundry, Anthropic, GCP Vertex AI, AWS Bedrock, and OpenRouter. 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.