DeepSeek: R1 vs Mistral: Mixtral 8x22B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: R1 (deepseek/deepseek-r1) vs Mistral: Mixtral 8x22B Instruct (mistralai/mixtral-8x22b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: R1 (deepseek/deepseek-r1) — Automatic Disk KV Cache ($0.35/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.07/1M input tokens (50% off $0.14 base) with zero code changes required, plus off-peak UTC scheduling discounts.
Mistral: Mixtral 8x22B Instruct (mistralai/mixtral-8x22b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Mixtral 8x22B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing DeepSeek: R1 (API ID: deepseek/deepseek-r1) vs Mistral: Mixtral 8x22B Instruct (API ID: mistralai/mixtral-8x22b-instruct), DeepSeek: R1 offers lower standard input pricing at $0.7/1M tokens ($2.5/1M output), while DeepSeek: R1 leads in cached prefix economics at $0.35/1M tokens (50% discount). DeepSeek: R1 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 | DeepSeek: R1 | Mistral: Mixtral 8x22B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-r1 | mistralai/mixtral-8x22b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.7 / $2.5 | $2 / $6 | DeepSeek: R1 |
| Cache Read Price (per 1M) | $0.35/1M (50% Off) | $1/1M (50% Off) | DeepSeek: R1 |
| Context Window / Max Output | 63K In / 16K Out | 64K In / 51K Out | Mistral: Mixtral 8x22B Instruct |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: R1 (-0ms) |
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf
Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency
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: R1 to Mistral: Mixtral 8x22B Instruct
Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency Verified P90 latency of 280ms.