Which is cheaper, GPT-5.3 Codex or Magistral Medium?
As of August 20, 2026, Magistral Medium is 56% cheaper on blended LLM API pricing. Magistral Medium costs $2.00 per million input tokens and $5.00 per million output tokens ($7.00 blended 1M-in + 1M-out). GPT-5.3 Codex costs $1.75 / $14.00 per million tokens ($15.75 blended). Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5.3 Codex vs Magistral Medium cost per million tokens?
GPT-5.3 Codex OpenAI API pricing is $1.75 input and $14.00 output per million tokens via OpenAI. Magistral Medium Mistral API pricing is $2.00 input and $5.00 output per million tokens via Mistral AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-5.3 Codex or Magistral Medium?
GPT-5.3 Codex has a published SWE-bench Verified score of 74.8%. Magistral Medium does not have that eval on this page yet.
What is the context window for GPT-5.3 Codex vs Magistral Medium?
GPT-5.3 Codex supports a 400K token context window, while Magistral Medium supports 40K tokens. GPT-5.3 Codex 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, GPT-5.3 Codex or Magistral Medium?
GPT-5.3 Codex leads on 3 of 3 shared benchmarks versus Magistral Medium'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 GPT-5.3 Codex or Magistral Medium better for production use?
Both GPT-5.3 Codex and Magistral Medium are production API models. For cost-sensitive production traffic, Magistral Medium 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 GPT-5.3 Codex and Magistral Medium in my app?
Yes. Call GPT-5.3 Codex through OpenAI and Magistral Medium through Mistral AI 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 GPT-5.3 Codex vs Magistral Medium pricing data?
List rates are the latest published OpenAI API pricing and Mistral API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-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 GPT-5.3 Codex and Magistral Medium?
GPT-5.3 Codex supports up to 128K output tokens per request, while Magistral Medium 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, GPT-5.3 Codex or Magistral Medium?
GPT-5.3 Codex has a measured throughput of approximately 50 tokens/second. Throughput data for Magistral Medium 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 GPT-5.3 Codex vs Magistral Medium comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5.3 Codex or Magistral Medium from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
