Mistral: Mistral Medium 3.5 vs Qwen: Qwen3 30B A3B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Mistral: Mistral Medium 3.5 (mistralai/mistral-medium-3-5) vs Qwen: Qwen3 30B A3B (qwen/qwen3-30b-a3b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Mistral: Mistral Medium 3.5 (mistralai/mistral-medium-3-5) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Mistral Medium 3.5: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.75/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3 30B A3B (qwen/qwen3-30b-a3b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3 30B A3B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.06/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Mistral: Mistral Medium 3.5 (API ID: mistralai/mistral-medium-3-5) vs Qwen: Qwen3 30B A3B (API ID: qwen/qwen3-30b-a3b), Qwen: Qwen3 30B A3B offers lower standard input pricing at $0.12/1M tokens ($0.5/1M output), while Qwen: Qwen3 30B A3B leads in cached prefix economics at $0.06/1M tokens (50% discount). Mistral: Mistral Medium 3.5 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 | Mistral: Mistral Medium 3.5 | Qwen: Qwen3 30B A3B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | mistralai/mistral-medium-3-5 | qwen/qwen3-30b-a3b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1.5 / $7.5 | $0.12 / $0.5 | Qwen: Qwen3 30B A3B |
| Cache Read Price (per 1M) | $0.75/1M (50% Off) | $0.06/1M (50% Off) | Qwen: Qwen3 30B A3B |
| Context Window / Max Output | 256K In / 205K Out | 40K In / 16K Out | Mistral: Mistral Medium 3.5 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Mistral: Mistral Medium 3.5 (-0ms) |
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
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, an
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 Mistral: Mistral Medium 3.5 to Qwen: Qwen3 30B A3B
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, an Verified P90 latency of 280ms.