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Magistral Small vs o3 Deep Research

Compare Mistral AI and OpenAI AI models

Mistral AI
Magistral Small
vs
OpenAI
o3 Deep Research

Cost Comparison (1000 input + 500 output tokens, 100 requests/day)

Magistral Small

Per Request:$0.001250
Daily:$0.125
Monthly:$3.75
Yearly:$45.625

o3 Deep Research

Per Request:$0.03
Daily:$3.00
Monthly:$90.00
Yearly:$1,095.00

Cost Differences

+$0.02875
Per Request
+$2.875
Daily
+$86.25
Monthly
+$1,049.375
Yearly

o3 Deep Research costs more than Magistral Small

Feature Comparison

FeatureMagistral Smallo3 Deep Research
ProviderMistral AIOpenAI
Input Price$0.50/1M tokens$10.00/1M tokens
Output Price$1.50/1M tokens$40.00/1M tokens
Context Window128,000 tokens200,000 tokens
Max Output16,384 tokens32,768 tokens
Categoryreasoningreasoning
Capabilities
textreasoning
textreasoningvisioncode
Release Date12/15/20256/26/2025

Magistral Small vs o3 Deep Research: Which Should You Choose?

Choosing between Magistral Small and o3 Deep Research depends on your priorities: cost efficiency, context length, or raw capability. Magistral Small is the more affordable option at $0.50/1M input tokens95% cheaper than o3 Deep Research. Meanwhile, o3 Deep Research offers a significantly larger context window at 200,000 tokens vs 128,000 for Magistral Small.

These models come from different providers — Mistral AI and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Mistral AI, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.

Both models are in the reasoning category, making this a direct head-to-head comparison. At scale — say 10,000 requests per day — the cost difference adds up: Magistral Small would save you roughly $8,625.00/month compared to o3 Deep Research. For startups and indie developers, that difference can be significant.

Output costs matter too. Magistral Small charges $1.50/1M output tokens vs $40.00 for o3 Deep Research. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Magistral Small has the edge here at $1.50/1M output tokens.

Multimodal capabilities: o3 Deep Research supports vision (image inputs) while Magistral Small is text-only. If your application needs image understanding, this narrows your choice.

Best Use Cases

Choose Magistral Small when:

  • • Budget is a primary concern
  • • You're already using Mistral AI's API ecosystem

Choose o3 Deep Research when:

  • • You need a larger context window (200,000 tokens)
  • • You need more capabilities (vision, code)
  • • You need longer outputs (up to 32,768 tokens)
  • • You're already using OpenAI's API ecosystem

Try Different Scenarios

Use the calculator below to see how costs change with different usage patterns

Magistral Small (Mistral AI)

o3 Deep Research (OpenAI)

Start using Magistral Small today

Sign Up for Mistral AI

Start using o3 Deep Research today

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Frequently Asked Questions

Which is cheaper, Magistral Small or o3 Deep Research?
Magistral Small is cheaper for input tokens at $0.50 per million tokens vs $10.00 for o3 Deep Research — that's 95% savings on input costs.
What is the context window difference between Magistral Small and o3 Deep Research?
Magistral Small supports 128,000 tokens while o3 Deep Research supports 200,000 tokens — a difference of 72,000 tokens in favor of o3 Deep Research.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Magistral Small is the lower-cost option, while o3 Deep Research offers a larger context window (200,000 vs 128,000 tokens). Choose Magistral Small for budget sensitivity or o3 Deep Research for longer context tasks.
Which model has better overall pricing for heavy usage?
At 100 requests/day with 1,000 input and 500 output tokens each, Magistral Small costs about $3.75/month and o3 Deep Research costs about $90.00/month. Overall, Magistral Small has lower combined input + output rates ($0.50 in, $1.50 out) vs o3 Deep Research.

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