Mistral Small 4 vs o4-mini
Mistral Small 4 vs o4-mini: Mistral Small 4 is cheaper for input-heavy usage ($0.15/M vs $1.10/M input tokens), while o4-mini is better for long-context tasks (2,000,000 tokens).
Direct answer: choose Mistral Small 4 for lower token spend and choose o4-mini 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)
Mistral Small 4
o4-mini
Cost Differences
o4-mini costs more than Mistral Small 4
Quick Recommendation
Winner for direct API pricing: Mistral Small 4. At the default workload, Mistral Small 4 saves about $8.55/month ($104.025/year) versus o4-mini.
Feature Comparison
| Feature | Mistral Small 4 | o4-mini |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Input Price | $0.15/1M tokens | $1.10/1M tokens |
| Output Price | $0.60/1M tokens | $4.40/1M tokens |
| Context Window | 128,000 tokens | 2,000,000 tokens |
| Max Output | 16,384 tokens | 131,072 tokens |
| Category | efficient | reasoning |
| Capabilities | textvisioncodereasoning | textreasoningcode |
| Release Date | 3/18/2026 | 4/16/2025 |
Mistral Small 4 vs o4-mini: Which Should You Choose?
Choosing between Mistral Small 4 and o4-mini depends on your priorities: cost efficiency, context length, or raw capability. Mistral Small 4 is the more affordable option at $0.15/1M input tokens — 86% cheaper than o4-mini. Meanwhile, o4-mini offers a significantly larger context window at 2,000,000 tokens vs 128,000 for Mistral Small 4.
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.
These models target different tiers: Mistral Small 4 is a efficient model while o4-mini is reasoning. This means they're optimized for different workloads. o4-mini targets more demanding workloads, while Mistral Small 4 provides a cost-effective option for everyday tasks.
Output costs matter too. Mistral Small 4 charges $0.60/1M output tokens vs $4.40 for o4-mini. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Mistral Small 4 has the edge here at $0.60/1M output tokens.
Multimodal capabilities: Mistral Small 4 supports vision (image inputs) while o4-mini is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Mistral Small 4 when:
- • Budget is a primary concern
- • You need more capabilities (vision)
- • You're already using Mistral AI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose o4-mini when:
- • You need a larger context window (2,000,000 tokens)
- • You need longer outputs (up to 131,072 tokens)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Mistral Small 4
- • Input pricing: $0.15/M tokens
- • Output pricing: $0.60/M tokens
- • Context window: 128,000 tokens
- • Max output: 16,384 tokens
Watch out for
- • Smaller context window than o4-mini
o4-mini
- • Input pricing: $1.10/M tokens
- • Output pricing: $4.40/M tokens
- • Context window: 2,000,000 tokens
- • Max output: 131,072 tokens
Watch out for
- • Higher input cost than Mistral Small 4
- • Higher output cost than Mistral Small 4
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Mistral Small 4 (Mistral AI)
o4-mini (OpenAI)
Start using Mistral Small 4 today
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Mistral Small 4 or o4-mini?▼
What is the context window difference between Mistral Small 4 and o4-mini?▼
Which model is better for AI Agent / Agentic Workflows?▼
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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