Llama 4 Scout vs Mistral Small 4
Two budget titans clash. Mistral Small 4 is 44% cheaper on input and 49% cheaper on output — but Llama 4 Scout has 7.8x more context. See which fits your workload.
Pricing data verified: 2026-06-20
| Specification | Llama 4 Scout (Meta) | Mistral Small 4 (Mistral) |
|---|---|---|
| Input Price (per 1M tokens) | $0.18 | $0.10 |
| Output Price (per 1M tokens) | $0.59 | $0.30 |
| Context Window | 1M | 128K |
| Tier | Budget | Budget |
| Provider | Meta (Together.ai) | Mistral |
Calculate Your Exact Costs
See how the costs stack up for your specific usage pattern.
Other Models to Consider
Which Model for Which Use Case?
High-Volume Classification
Mistral Small 4's 44% cheaper input pricing makes it ideal for classification tasks processing millions of short inputs daily. Fast, cheap, and accurate.
Long Document Processing
Llama 4 Scout's 1M context window (7.8x larger than Mistral's 128K) handles lengthy documents, books, and large codebases in a single pass.
Chatbots on a Budget
Mistral Small 4's 49% cheaper output makes it the clear winner for chatbots where output cost dominates. Shorter context is fine for most conversations.
Code Review with Large Repos
Llama 4 Scout's 1M context window can ingest entire repositories for holistic code review. Mistral's 128K may truncate large files.
Comparing Budget Models?
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Frequently Asked Questions
Is Mistral Small 4 cheaper than Llama 4 Scout?
Yes. Mistral Small 4 is 44% cheaper on input ($0.10/M vs $0.18/M) and 49% cheaper on output ($0.30/M vs $0.59/M). However, Llama 4 Scout has 7.8x more context (1M vs 128K).
When should I choose Llama 4 Scout over Mistral Small 4?
Choose Llama 4 Scout when you need long context support (1M vs 128K). It excels for large codebases, long document processing, and use cases where context window size matters more than per-token cost.
Which model is better for coding?
Both are capable for coding tasks. Llama 4 Scout's 1M context window is advantageous for large codebases, while Mistral Small 4's lower cost makes it better for high-volume code generation tasks.
Can I self-host these models?
Llama 4 Scout is fully open-source and can be self-hosted on your own infrastructure. Mistral Small 4 has weights available as well, offering flexibility for on-premise deployment.