Which is cheaper, Mistral Medium 3.5 or o1-pro?
As of August 20, 2026, Mistral Medium 3.5 is 99% cheaper on blended LLM API pricing. Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens ($9.00 blended 1M-in + 1M-out). o1-pro costs $150.00 / $600.00 per million tokens ($750.00 blended). Sources: https://docs.mistral.ai/platform/pricing/ and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Mistral Medium 3.5 vs o1-pro cost per million tokens?
Mistral Medium 3.5 Mistral API pricing is $1.50 input and $7.50 output per million tokens via Mistral AI. o1-pro OpenAI API pricing is $150.00 input and $600.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Mistral Medium 3.5 or o1-pro?
Mistral Medium 3.5 has a published SWE-bench Verified score of 77.6%. o1-pro does not have that eval on this page yet.
What is the context window for Mistral Medium 3.5 vs o1-pro?
Mistral Medium 3.5 supports a 256K token context window, while o1-pro supports 200K tokens. Mistral Medium 3.5 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, Mistral Medium 3.5 or o1-pro?
Shared benchmark scores for Mistral Medium 3.5 and o1-pro are still limited. Check the comparison table for the evals each model has published. 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 Mistral Medium 3.5 or o1-pro better for production use?
Both Mistral Medium 3.5 and o1-pro are production API models. For cost-sensitive production traffic, Mistral Medium 3.5 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 Mistral Medium 3.5 and o1-pro in my app?
Yes. Call Mistral Medium 3.5 through Mistral AI and o1-pro through OpenAI 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 Mistral Medium 3.5 vs o1-pro pricing data?
List rates are the latest published Mistral API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://docs.mistral.ai/platform/pricing/ and https://developers.openai.com/api/docs/pricing. 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 Mistral Medium 3.5 and o1-pro?
Mistral Medium 3.5 supports up to 256K output tokens per request, while o1-pro supports up to 100K 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, Mistral Medium 3.5 or o1-pro?
Mistral Medium 3.5 has a measured throughput of approximately 0.9605563235026328 tokens/second. Throughput data for o1-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 Mistral Medium 3.5 vs o1-pro comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Mistral Medium 3.5 or o1-pro from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
