As of August 25, 2026, o4-mini is 39% cheaper per million tokens than Mistral Medium 3.5. Mistral Medium 3.5 is $1.50 / $7.50 per million input/output tokens versus o4-mini at $1.10 / $4.40. Sources: https://docs.mistral.ai/platform/pricing/ and https://developers.openai.com/api/docs/pricing
Sources: Mistral AI pricing (https://docs.mistral.ai/platform/pricing/); OpenAI API pricing (https://developers.openai.com/api/docs/pricing)
Mistral Medium 3.5
Mistral
Input
$1.50
Output
$7.50
o4-mini
OpenAI
Input
$1.10
Output
$4.40
Token pricing, specs, and benchmarks side by side
Each bar is share of the current leader on that eval. Click a row to open the board.
SWE-bench Verified. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.
Mistral Medium 3.5o4-miniVerdict
o4-mini offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.
As of August 25, 2026, o4-mini is 39% cheaper on blended LLM API pricing. o4-mini costs $1.10 per million input tokens and $4.40 per million output tokens ($5.50 blended 1M-in + 1M-out). Mistral Medium 3.5 costs $1.50 / $7.50 per million tokens ($9.00 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.
Mistral Medium 3.5 Mistral API pricing is $1.50 input and $7.50 output per million tokens via Mistral AI. o4-mini OpenAI API pricing is $1.10 input and $4.40 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Mistral Medium 3.5 leads on SWE-bench Verified: Mistral Medium 3.5 at 77.6% vs o4-mini at 68.1%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Mistral Medium 3.5 supports a 256K token context window, while o4-mini 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.
o4-mini leads on 10 of 11 shared benchmarks versus Mistral Medium 3.5's 1 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.
Both Mistral Medium 3.5 and o4-mini are production API models. For cost-sensitive production traffic, o4-mini 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.
Yes. Call Mistral Medium 3.5 through Mistral AI and o4-mini 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.
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.
Mistral Medium 3.5 supports up to 256K output tokens per request, while o4-mini 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.
Mistral Medium 3.5 runs at approximately 1 tokens/second while o4-mini runs at 115 tokens/second. o4-mini is faster in raw throughput. 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.
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 o4-mini from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Mistral Medium 3.5 costs $1.50/M input and $7.50/M output via Mistral AI. o4-mini costs $1.10/M input and $4.40/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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