Magistral Small vs o3 Deep Research
Magistral Small vs o3 Deep Research: Magistral Small is cheaper for input-heavy usage ($0.50/M vs $10.00/M input tokens), while o3 Deep Research is better for long-context tasks (200,000 tokens).
Direct answer: choose Magistral Small for lower token spend and choose o3 Deep Research when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Magistral Small
o3 Deep Research
Cost Differences
o3 Deep Research costs more than Magistral Small
Quick Recommendation
Winner for direct API pricing: Magistral Small. At the default workload, Magistral Small saves about $86.25/month ($1,049.375/year) versus o3 Deep Research.
Feature Comparison
| Feature | Magistral Small | o3 Deep Research |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Input Price | $0.50/1M tokens | $10.00/1M tokens |
| Output Price | $1.50/1M tokens | $40.00/1M tokens |
| Context Window | 128,000 tokens | 200,000 tokens |
| Max Output | 16,384 tokens | 32,768 tokens |
| Category | reasoning | reasoning |
| Capabilities | textreasoning | textreasoningvisioncode |
| Release Date | 12/15/2025 | 6/26/2025 |
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 tokens — 95% 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
Pros and Caveats at a Glance
Magistral Small
- • Input pricing: $0.50/M tokens
- • Output pricing: $1.50/M tokens
- • Context window: 128,000 tokens
- • Max output: 16,384 tokens
Watch out for
- • Smaller context window than o3 Deep Research
o3 Deep Research
- • Input pricing: $10.00/M tokens
- • Output pricing: $40.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher input cost than Magistral Small
- • Higher output cost than Magistral Small
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Magistral Small (Mistral AI)
o3 Deep Research (OpenAI)
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Which is cheaper, Magistral Small or o3 Deep Research?▼
What is the context window difference between Magistral Small and o3 Deep Research?▼
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Which model has better overall pricing for heavy usage?▼
Where can I compare Mistral AI and OpenAI API pricing beyond this model matchup?▼
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