Codestral vs Llama 4 Scout
Compare Mistral AI and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codestral
Llama 4 Scout
Cost Differences
Llama 4 Scout costs less than Codestral
Feature Comparison
| Feature | Codestral | Llama 4 Scout |
|---|---|---|
| Provider | Mistral AI | Meta (via Together AI) |
| Input Price | $0.30/1M tokens | $0.08/1M tokens |
| Output Price | $0.90/1M tokens | $0.30/1M tokens |
| Context Window | 128,000 tokens | 10,000,000 tokens |
| Max Output | 32,768 tokens | 32,768 tokens |
| Category | balanced | efficient |
| Capabilities | textcode | textvisioncode |
| Release Date | 7/30/2025 | 4/5/2025 |
Codestral vs Llama 4 Scout: Which Should You Choose?
Choosing between Codestral and Llama 4 Scout depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Scout is the more affordable option at $0.08/1M input tokens — 73% cheaper than Codestral. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 tokens vs 128,000 for Codestral.
These models come from different providers — Mistral AI and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Mistral AI, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Codestral is a balanced model while Llama 4 Scout is efficient. This means they're optimized for different workloads. Llama 4 Scout targets more demanding workloads, while Codestral provides a cost-effective option for everyday tasks.
Output costs matter too. Codestral charges $0.90/1M output tokens vs $0.30 for Llama 4 Scout. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Scout has the edge here at $0.30/1M output tokens.
Multimodal capabilities: Llama 4 Scout supports vision (image inputs) while Codestral is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Codestral when:
- • You're already using Mistral AI's API ecosystem
Choose Llama 4 Scout when:
- • Budget is a primary concern
- • You need a larger context window (10,000,000 tokens)
- • You need more capabilities (vision)
- • You're already using Meta (via Together AI)'s API ecosystem
- • You're running high-volume, latency-sensitive workloads
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Codestral (Mistral AI)
Llama 4 Scout (Meta (via Together AI))
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