Which is cheaper, MiMo-V2.5-Pro or Phi-3.5-mini-instruct?
As of August 25, 2026, Phi-3.5-mini-instruct is 85% cheaper on blended LLM API pricing. Phi-3.5-mini-instruct costs $0.10 per million input tokens and $0.10 per million output tokens ($0.20 blended 1M-in + 1M-out). MiMo-V2.5-Pro costs $0.43 / $0.87 per million tokens ($1.30 blended). Sources: https://anotherwrapper.com/tools/llm-pricing and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does MiMo-V2.5-Pro vs Phi-3.5-mini-instruct cost per million tokens?
MiMo-V2.5-Pro Xiaomi API pricing is $0.43 input and $0.87 output per million tokens via Xiaomi. Phi-3.5-mini-instruct Microsoft API pricing is $0.10 input and $0.10 output per million tokens via Microsoft. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, MiMo-V2.5-Pro or Phi-3.5-mini-instruct?
MiMo-V2.5-Pro has a published SWE-bench Verified score of 78.9%. Phi-3.5-mini-instruct does not have that eval on this page yet.
What is the context window for MiMo-V2.5-Pro vs Phi-3.5-mini-instruct?
MiMo-V2.5-Pro supports a 1M token context window, while Phi-3.5-mini-instruct supports 128K tokens. MiMo-V2.5-Pro offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, MiMo-V2.5-Pro or Phi-3.5-mini-instruct?
MiMo-V2.5-Pro leads on 10 of 10 shared benchmarks versus Phi-3.5-mini-instruct's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is MiMo-V2.5-Pro or Phi-3.5-mini-instruct better for production use?
Both MiMo-V2.5-Pro and Phi-3.5-mini-instruct are production API models. For cost-sensitive production traffic, Phi-3.5-mini-instruct has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between MiMo-V2.5-Pro and Phi-3.5-mini-instruct in my app?
Yes. Call MiMo-V2.5-Pro through Xiaomi and Phi-3.5-mini-instruct through Microsoft with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this MiMo-V2.5-Pro vs Phi-3.5-mini-instruct pricing data?
List rates are the latest published Xiaomi API pricing and Microsoft API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-pricing and https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for MiMo-V2.5-Pro and Phi-3.5-mini-instruct?
MiMo-V2.5-Pro supports up to 131K output tokens per request, while Phi-3.5-mini-instruct supports up to 128K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, MiMo-V2.5-Pro or Phi-3.5-mini-instruct?
Phi-3.5-mini-instruct has a measured throughput of approximately 23 tokens/second. Throughput data for MiMo-V2.5-Pro is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this MiMo-V2.5-Pro vs Phi-3.5-mini-instruct comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open MiMo-V2.5-Pro or Phi-3.5-mini-instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
