Mistral Large 2 vs Phi 3.5 MoE Instruct
Mistral Large 2 (2025) and Phi 3.5 MoE Instruct (2024) are compact production models from MistralAI and Microsoft Research. Mistral Large 2 ships a 128K-token context window, while Phi 3.5 MoE Instruct ships a 128K-token context window. On pricing, Mistral Large 2 costs $0.48/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral Large 2 is safer overall; choose Phi 3.5 MoE Instruct when provider fit matters.
Specs
| Released | 2025-11-25 | 2024-08-20 |
| Context window | 128K | 128K |
| Parameters | 123B | 16x3.8B (42B, 6.6B active) |
| Architecture | decoder only | decoder only |
| License | True | MIT |
| Knowledge cutoff | 2025-07 | - |
Pricing and availability
| Mistral Large 2 | Phi 3.5 MoE Instruct | |
|---|---|---|
| Input price | $0.48/1M tokens | $0.5/1M tokens |
| Output price | $2.4/1M tokens | $0.5/1M tokens |
| Providers |
Capabilities
| Mistral Large 2 | Phi 3.5 MoE Instruct | |
|---|---|---|
| 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: Mistral Large 2, multimodal input: Mistral Large 2, function calling: Mistral Large 2, tool use: Mistral Large 2, and structured outputs: Mistral Large 2. 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 2 lists $0.48/1M input and $2.4/1M output tokens, while Phi 3.5 MoE Instruct lists $0.5/1M input and $0.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi 3.5 MoE Instruct lower by about $0.56 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.
Choose Mistral Large 2 when vision-heavy evaluation, lower input-token cost, and broader provider choice are central to the workload. Choose Phi 3.5 MoE Instruct when provider fit 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.
FAQ
Which has a larger context window, Mistral Large 2 or Phi 3.5 MoE Instruct?
Mistral Large 2 supports 128K tokens, while Phi 3.5 MoE Instruct supports 128K 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 2 or Phi 3.5 MoE Instruct?
Mistral Large 2 is cheaper on tracked token pricing. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Phi 3.5 MoE Instruct costs $0.5/1M input and $0.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 2 or Phi 3.5 MoE Instruct open source?
Mistral Large 2 is listed under True. Phi 3.5 MoE Instruct is listed under MIT. 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 2 or Phi 3.5 MoE Instruct?
Mistral Large 2 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, Mistral Large 2 or Phi 3.5 MoE Instruct?
Mistral Large 2 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 Mistral Large 2 and Phi 3.5 MoE Instruct?
Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Phi 3.5 MoE Instruct is available on Fireworks AI. 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.