Mistral: Devstral 2 2512 vs Meta: Llama 4 Scout: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Mistral: Devstral 2 2512 (mistralai/devstral-2512) vs Meta: Llama 4 Scout (meta-llama/llama-4-scout). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Mistral: Devstral 2 2512 (mistralai/devstral-2512) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Devstral 2 2512: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.2/1M) or route via asynchronous Batch API for 50% off standard token rates.
Meta: Llama 4 Scout (meta-llama/llama-4-scout) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 4 Scout: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.09/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Mistral: Devstral 2 2512 (API ID: mistralai/devstral-2512) vs Meta: Llama 4 Scout (API ID: meta-llama/llama-4-scout), Meta: Llama 4 Scout offers lower standard input pricing at $0.18/1M tokens ($0.59/1M output), while Meta: Llama 4 Scout leads in cached prefix economics at $0.09/1M tokens (50% discount). Mistral: Devstral 2 2512 achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
Auto-discovered via live global telemetry registry.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Mistral: Devstral 2 2512 | Meta: Llama 4 Scout | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | mistralai/devstral-2512 | meta-llama/llama-4-scout | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.4 / $2 | $0.18 / $0.59 | Meta: Llama 4 Scout |
| Cache Read Price (per 1M) | $0.2/1M (50% Off) | $0.09/1M (50% Off) | Meta: Llama 4 Scout |
| Context Window / Max Output | 256K In / 205K Out | 1280K In / 115K Out | Mistral: Devstral 2 2512 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Mistral: Devstral 2 2512 (-0ms) |
Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. De
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimo
Real-Time Stack Cost & Hidden-Fee Simulator (MAU / Token / Egress / GMV)
Calibrated with Reddit r/FinOps & r/devops telemetry: Includes Context Caching, Bandwidth Egress, and MoR Tax
🛰️Switch from Mistral: Devstral 2 2512 to Meta: Llama 4 Scout
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimo Verified P90 latency of 280ms.