Devstral 2 vs Llama 4 Scout
Compare Mistral AI and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Devstral 2
Llama 4 Scout
Cost Differences
Llama 4 Scout costs less than Devstral 2
Feature Comparison
| Feature | Devstral 2 | Llama 4 Scout |
|---|---|---|
| Provider | Mistral AI | Meta (via Together AI) |
| Input Price | $0.40/1M tokens | $0.08/1M tokens |
| Output Price | $0.90/1M tokens | $0.30/1M tokens |
| Context Window | 262,144 tokens | 10,000,000 tokens |
| Max Output | 32,768 tokens | 32,768 tokens |
| Category | efficient | efficient |
| Capabilities | textcode | textvisioncode |
| Release Date | 12/9/2025 | 4/5/2025 |
Devstral 2 vs Llama 4 Scout: Which Should You Choose?
Choosing between Devstral 2 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 — 80% cheaper than Devstral 2. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 tokens vs 262,144 for Devstral 2.
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.
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: Llama 4 Scout would save you roughly $186.00/month compared to Devstral 2. For startups and indie developers, that difference can be significant.
Output costs matter too. Devstral 2 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 Devstral 2 is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Devstral 2 when:
- • You're already using Mistral AI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
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
Devstral 2 (Mistral AI)
Llama 4 Scout (Meta (via Together AI))
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