Which is cheaper, MAI-Code-1.1-Flash or MAI-Thinking-1?
As of August 30, 2026, MAI-Thinking-1 is 46% cheaper on blended LLM API pricing. MAI-Thinking-1 costs $0.15 per million input tokens and $0.60 per million output tokens ($0.75 blended 1M-in + 1M-out). MAI-Code-1.1-Flash costs $0.20 / $1.20 per million tokens ($1.40 blended). Sources: https://ai.azure.com and https://azure.microsoft.com/pricing/details/azure-openai-service/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does MAI-Code-1.1-Flash vs MAI-Thinking-1 cost per million tokens?
MAI-Code-1.1-Flash Microsoft API pricing is $0.20 input and $1.20 output per million tokens via Microsoft. MAI-Thinking-1 Microsoft API pricing is $0.15 input and $0.60 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, MAI-Code-1.1-Flash or MAI-Thinking-1?
MAI-Thinking-1 leads on SWE-bench Verified: MAI-Code-1.1-Flash at 72.6% vs MAI-Thinking-1 at 73.5%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for MAI-Code-1.1-Flash vs MAI-Thinking-1?
MAI-Code-1.1-Flash supports a 256K token context window, while MAI-Thinking-1 supports 128K tokens. MAI-Code-1.1-Flash 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, MAI-Code-1.1-Flash or MAI-Thinking-1?
MAI-Thinking-1 leads on 1 of 1 shared benchmarks versus MAI-Code-1.1-Flash'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 MAI-Code-1.1-Flash or MAI-Thinking-1 better for production use?
Both MAI-Code-1.1-Flash and MAI-Thinking-1 are production API models. For cost-sensitive production traffic, MAI-Thinking-1 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 MAI-Code-1.1-Flash and MAI-Thinking-1 in my app?
Yes. Call MAI-Code-1.1-Flash through Microsoft and MAI-Thinking-1 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 MAI-Code-1.1-Flash vs MAI-Thinking-1 pricing data?
List rates are the latest published Microsoft API pricing and Microsoft API pricing, quoted per million tokens. Official rate sheets: https://ai.azure.com and https://azure.microsoft.com/pricing/details/azure-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 MAI-Code-1.1-Flash and MAI-Thinking-1?
MAI-Code-1.1-Flash supports up to an unspecified number of output tokens per request, while MAI-Thinking-1 supports up to an unspecified number of 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, MAI-Code-1.1-Flash or MAI-Thinking-1?
Neither MAI-Code-1.1-Flash nor MAI-Thinking-1 has published throughput data on this page yet. 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 MAI-Code-1.1-Flash vs MAI-Thinking-1 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open MAI-Code-1.1-Flash or MAI-Thinking-1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
