Llama 4 Maverick vs Mistral Small 4
Two budget-friendly options for cost-conscious builders. Mistral Small 4 is 63% cheaper on input and 73% cheaper on output — but Llama 4 Maverick offers an 8x larger context window.
Pricing data verified: 2026-06-20
| Specification | Llama 4 Maverick (Meta) | Mistral Small 4 (Mistral) |
|---|---|---|
| Input Price (per 1M tokens) | $0.27 | $0.10 |
| Output Price (per 1M tokens) | $1.10 | $0.30 |
| Context Window | 1M | 128K |
| Tier | Budget | Budget |
| Provider | Meta | Mistral |
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See how the costs stack up for your specific usage pattern.
Other Models to Consider
Which Model for Which Use Case?
Ultra-Low-Cost API
Mistral Small 4 at $0.10/$0.30 is the cheapest option available. For high-volume classification, routing, or simple generation tasks, it can't be beat on price.
Long Context Processing
Llama 4 Maverick's 1M context window handles entire codebases, legal documents, and long conversations. Mistral Small 4's 128K may require chunking.
Self-Hosting / On-Premise
Both models are open-weight, but Meta's Llama ecosystem has broader community support for self-hosting with tools like vLLM, TGI, and Ollama.
Budget-Constrained Startup
If you're bootstrapping and need to minimize costs, Mistral Small 4 at $0.10/M input gives you the most tokens per dollar of any model.
Comparing Meta vs Mistral Models?
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Frequently Asked Questions
Is Mistral Small 4 cheaper than Llama 4 Maverick?
Yes. Mistral Small 4 costs $0.10/M input and $0.30/M output — 63% cheaper on input and 73% cheaper on output than Llama 4 Maverick's $0.27/M input and $1.10/M output.
When would I choose Llama 4 Maverick over Mistral Small 4?
Choose Llama 4 Maverick if you need a larger 1M context window (vs Mistral's 128K), prefer Meta's open-source ecosystem for self-hosting, or need Maverick's stronger performance on complex reasoning tasks.
Which model has a larger context window?
Llama 4 Maverick has a 1M token context window — nearly 8x larger than Mistral Small 4's 128K context window. This makes Maverick better for processing long documents and multi-turn conversations.