DeepSeek-V4 Flash vs Meta: Muse Spark Open: Live Promos, Pricing, Hidden Fees & Latency
DeepSeek-V4 Flash (deepseek-v4-flash) — Automatic Disk KV Cache (0.003/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.022/1M off-peak input tokens (vs $0.66 off-peak base) with zero code changes required, plus off-peak UTC scheduling discounts.
Meta: Muse Spark Open (meta/muse-spark-open) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Spark Open: 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.
In Etuki October 2026 FinOps telemetry comparing DeepSeek-V4 Flash (API ID: deepseek-v4-flash) vs Meta: Muse Spark Open (API ID: meta/muse-spark-open), DeepSeek-V4 Flash offers lower standard input pricing at $0.15/1M tokens ($0.6/1M output), while DeepSeek-V4 Flash leads in cached prefix economics at $0.003/1M tokens (50% discount). DeepSeek-V4 Flash achieves a 165ms faster P90 time-to-first-token latency (115ms vs 280ms).
Official disk-KV cache hit is $0.006/1M (91.4% off). Subject to DeepSeek Beijing peak/off-peak scheduling multipliers.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | DeepSeek-V4 Flash | Meta: Muse Spark Open | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek-v4-flash | meta/muse-spark-open | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $0.6 | $1.25 / $4.25 | DeepSeek-V4 Flash |
| Cache Read Price (per 1M) | $0.003/1M (50% Off) | $0.625/1M (50% Off) | DeepSeek-V4 Flash |
| Context Window / Max Output | 1024K In / 922K Out | 1024K In / 922K Out | DeepSeek-V4 Flash |
| P90 First-Token / Edge Latency | 115ms | 280ms | DeepSeek-V4 Flash (-165ms) |
DeepSeek Jul 31, 2026 ultra-fast model ($0.07/$0.14 base, Official Cache Hit $0.006/1M, Peak 09:00-12:00 & 14:00-18:00 BJ dynamic pricing). Upgraded by V4.1-Flash-1017.
Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and de
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 DeepSeek-V4 Flash to Meta: Muse Spark Open
Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and de Verified P90 latency of 280ms.