Mistral Large vs Phi-3 Mini 4k
Mistral Large (2024) and Phi-3 Mini 4k (2024) are compact production models from MistralAI and Microsoft Research. Mistral Large ships a 32k-token context window, while Phi-3 Mini 4k ships a 4K-token context window. On MMLU PRO, Mistral Large leads by 5.8 pts. On pricing, Phi-3 Mini 4k costs $0.05/1M input tokens versus $0.32/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Phi-3 Mini 4k is ~540% cheaper at $0.05/1M; pay for Mistral Large only for long-context analysis.
Specs
| Released | 2024-02-08 | 2024-04-23 |
| Context window | 32k | 4K |
| Parameters | — | 3.8B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2024-03 | - |
Pricing and availability
| Mistral Large | Phi-3 Mini 4k | |
|---|---|---|
| Input price | $0.32/1M tokens | $0.05/1M tokens |
| Output price | $0.96/1M tokens | $0.25/1M tokens |
| Providers |
Capabilities
| Mistral Large | Phi-3 Mini 4k | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Mistral Large | Phi-3 Mini 4k |
|---|---|---|
| MMLU PRO | 51.5 | 45.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has Mistral Large at 51.5 and Phi-3 Mini 4k at 45.7, with Mistral Large ahead by 5.8 points. The largest visible gap is 5.8 points on MMLU PRO, 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 vision: Mistral Large, function calling: Mistral Large, tool use: Mistral Large, and structured outputs: Mistral Large. 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, Mistral Large lists $0.32/1M input and $0.96/1M output tokens, while Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-3 Mini 4k lower by about $0.4 per million blended tokens. Availability is 8 providers versus 4, so concentration risk also matters.
Choose Mistral Large when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Phi-3 Mini 4k when provider fit 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.
FAQ
Which has a larger context window, Mistral Large or Phi-3 Mini 4k?
Mistral Large supports 32k tokens, while Phi-3 Mini 4k supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mistral Large or Phi-3 Mini 4k?
Phi-3 Mini 4k is cheaper on tracked token pricing. Mistral Large costs $0.32/1M input and $0.96/1M output tokens. Phi-3 Mini 4k costs $0.05/1M input and $0.25/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large or Phi-3 Mini 4k open source?
Mistral Large is listed under Proprietary. Phi-3 Mini 4k is listed under Open Source. 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, Mistral Large or Phi-3 Mini 4k?
Mistral Large 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 function calling, Mistral Large or Phi-3 Mini 4k?
Mistral Large 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 Mistral Large and Phi-3 Mini 4k?
Mistral Large is available on NVIDIA NIM, Microsoft Foundry, AWS Bedrock, Mistral AI Studio, and IBM watsonx. Phi-3 Mini 4k is available on Microsoft Foundry, NVIDIA NIM, Baseten 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.