GPT-5.4 nano vs Mistral Small 3.2
GPT-5.4 nano vs Mistral Small 3.2: Mistral Small 3.2 is cheaper for input-heavy usage ($0.10/M vs $0.20/M input tokens), while GPT-5.4 nano is better for long-context tasks (128,000 tokens).
Direct answer: choose Mistral Small 3.2 for lower token spend and choose GPT-5.4 nano 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)
GPT-5.4 nano
Mistral Small 3.2
Cost Differences
Mistral Small 3.2 costs less than GPT-5.4 nano
Quick Recommendation
Winner for direct API pricing: Mistral Small 3.2. At the default workload, Mistral Small 3.2 saves about $1.725/month ($20.9875/year) versus GPT-5.4 nano.
Feature Comparison
| Feature | GPT-5.4 nano | Mistral Small 3.2 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Input Price | $0.20/1M tokens | $0.10/1M tokens |
| Output Price | $1.25/1M tokens | $0.30/1M tokens |
| Context Window | 128,000 tokens | 128,000 tokens |
| Max Output | 8,192 tokens | 8,192 tokens |
| Category | efficient | efficient |
| Capabilities | text | textcode |
| Release Date | 3/6/2026 | 12/2/2025 |
GPT-5.4 nano vs Mistral Small 3.2: Which Should You Choose?
Choosing between GPT-5.4 nano and Mistral Small 3.2 depends on your priorities: cost efficiency, context length, or raw capability. Mistral Small 3.2 is the more affordable option at $0.10/1M input tokens — 50% cheaper than GPT-5.4 nano.
These models come from different providers — OpenAI and Mistral AI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with OpenAI, switching to Mistral AIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
Both models are in the efficient category, making this a direct head-to-head comparison. At scale — say 10,000 requests per day — the cost difference adds up: Mistral Small 3.2 would save you roughly $172.50/month compared to GPT-5.4 nano. For startups and indie developers, that difference can be significant.
Output costs matter too. GPT-5.4 nano charges $1.25/1M output tokens vs $0.30 for Mistral Small 3.2. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Mistral Small 3.2 has the edge here at $0.30/1M output tokens.
Best Use Cases
Choose GPT-5.4 nano when:
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Mistral Small 3.2 when:
- • Budget is a primary concern
- • You need more capabilities (code)
- • You're already using Mistral AI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Pros and Caveats at a Glance
GPT-5.4 nano
- • Input pricing: $0.20/M tokens
- • Output pricing: $1.25/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Higher input cost than Mistral Small 3.2
- • Higher output cost than Mistral Small 3.2
Mistral Small 3.2
- • Input pricing: $0.10/M tokens
- • Output pricing: $0.30/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Trade-offs are minor in this matchup.
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5.4 nano (OpenAI)
Mistral Small 3.2 (Mistral AI)
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Which is cheaper, GPT-5.4 nano or Mistral Small 3.2?▼
What is the context window difference between GPT-5.4 nano and Mistral Small 3.2?▼
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