Meta: Muse Spark 1.2 vs Mistral: Mistral Medium 3.5 (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Muse Spark 1.2 (meta/muse-spark-1.2) vs Mistral: Mistral Medium 3.5 (batch) (mistralai/mistral-medium-3-5:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Muse Spark 1.2 (meta/muse-spark-1.2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Spark 1.2: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.625/1M) or route via asynchronous Batch API for 50% off standard token rates.
Mistral: Mistral Medium 3.5 (batch) (mistralai/mistral-medium-3-5:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Mistral Medium 3.5 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.375/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Muse Spark 1.2 (API ID: meta/muse-spark-1.2) vs Mistral: Mistral Medium 3.5 (batch) (API ID: mistralai/mistral-medium-3-5:batch), Mistral: Mistral Medium 3.5 (batch) offers lower standard input pricing at $0.75/1M tokens ($3.75/1M output), while Mistral: Mistral Medium 3.5 (batch) leads in cached prefix economics at $0.375/1M tokens (50% discount). Meta: Muse Spark 1.2 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: Muse Spark 1.2 | Mistral: Mistral Medium 3.5 (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta/muse-spark-1.2 | mistralai/mistral-medium-3-5:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1.25 / $4.25 | $0.75 / $3.75 | Mistral: Mistral Medium 3.5 (batch) |
| Cache Read Price (per 1M) | $0.625/1M (50% Off) | $0.375/1M (50% Off) | Mistral: Mistral Medium 3.5 (batch) |
| Context Window / Max Output | 1024K In / 922K Out | 256K In / 205K Out | Meta: Muse Spark 1.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Muse Spark 1.2 (-0ms) |
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context wi
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, a
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: Muse Spark 1.2 to Mistral: Mistral Medium 3.5 (batch)
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, a Verified P90 latency of 280ms.