Recursive: Flint (free) vs DeepSeek: DeepSeek V3.2: Live Promos, Pricing, Hidden Fees & Latency
Recursive: Flint (free) (recursive/flint-v1.0:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Recursive: Flint (free): Activate ephemeral prefix caching to slash input costs by 50% (down to 0/1M) or route via asynchronous Batch API for 50% off standard token rates.
DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) — Automatic Disk KV Cache (0.028/1M) & 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.
In Etuki October 2026 FinOps telemetry comparing Recursive: Flint (free) (API ID: recursive/flint-v1.0:free) vs DeepSeek: DeepSeek V3.2 (API ID: deepseek/deepseek-v3.2), Recursive: Flint (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while Recursive: Flint (free) leads in cached prefix economics at $0/1M tokens (50% discount). Recursive: Flint (free) 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 | Recursive: Flint (free) | DeepSeek: DeepSeek V3.2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | recursive/flint-v1.0:free | deepseek/deepseek-v3.2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0 / $0 | $0.28 / $0.42 | Recursive: Flint (free) |
| Cache Read Price (per 1M) | $0/1M (50% Off) | $0.028/1M (50% Off) | Recursive: Flint (free) |
| Context Window / Max Output | 256K In / 230K Out | 160K In / 64K Out | Recursive: Flint (free) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Recursive: Flint (free) (-0ms) |
Flint is an open-weight mixture-of-experts model from Recursive, with about 2.5B active parameters out of 40B total, built by Recursive's autoresearch system Eureka Machine for cod
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse At
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 Recursive: Flint (free) to DeepSeek: DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse At Verified P90 latency of 280ms.