Meta: Llama 4 Maverick vs Mistral: Codestral 2508 (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama 4 Maverick (meta-llama/llama-4-maverick) vs Mistral: Codestral 2508 (batch) (mistralai/codestral-2508:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Llama 4 Maverick (meta-llama/llama-4-maverick) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 4 Maverick: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0938/1M) or route via asynchronous Batch API for 50% off standard token rates.
Mistral: Codestral 2508 (batch) (mistralai/codestral-2508:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Codestral 2508 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.075/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 4 Maverick (API ID: meta-llama/llama-4-maverick) vs Mistral: Codestral 2508 (batch) (API ID: mistralai/codestral-2508:batch), Mistral: Codestral 2508 (batch) offers lower standard input pricing at $0.15/1M tokens ($0.45/1M output), while Mistral: Codestral 2508 (batch) leads in cached prefix economics at $0.075/1M tokens (50% discount). Meta: Llama 4 Maverick 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 | Meta: Llama 4 Maverick | Mistral: Codestral 2508 (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-4-maverick | mistralai/codestral-2508:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1875 / $0.6525 | $0.15 / $0.45 | Mistral: Codestral 2508 (batch) |
| Cache Read Price (per 1M) | $0.0938/1M (50% Off) | $0.075/1M (50% Off) | Mistral: Codestral 2508 (batch) |
| Context Window / Max Output | 1024K In / 16K Out | 250K In / 200K Out | Mistral: Codestral 2508 (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 4 Maverick (-0ms) |
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correc
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 Meta: Llama 4 Maverick to Mistral: Codestral 2508 (batch)
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correc Verified P90 latency of 280ms.