SpaceXAI: Grok 4.3 (batch) vs Reka Edge: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing SpaceXAI: Grok 4.3 (batch) (x-ai/grok-4.3:batch) vs Reka Edge (rekaai/reka-edge). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
SpaceXAI: Grok 4.3 (batch) (x-ai/grok-4.3:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for SpaceXAI: Grok 4.3 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
Reka Edge (rekaai/reka-edge) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Reka Edge: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing SpaceXAI: Grok 4.3 (batch) (API ID: x-ai/grok-4.3:batch) vs Reka Edge (API ID: rekaai/reka-edge), Reka Edge offers lower standard input pricing at $0.1/1M tokens ($0.1/1M output), while Reka Edge leads in cached prefix economics at $0.05/1M tokens (50% discount). SpaceXAI: Grok 4.3 (batch) 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 | SpaceXAI: Grok 4.3 (batch) | Reka Edge | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | x-ai/grok-4.3:batch | rekaai/reka-edge | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $2 | $0.1 / $0.1 | Reka Edge |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.05/1M (50% Off) | Reka Edge |
| Context Window / Max Output | 977K In / 879K Out | 16K In / 14K Out | SpaceXAI: Grok 4.3 (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | SpaceXAI: Grok 4.3 (batch) (-0ms) |
Grok 4.3 is a reasoning model from SpaceXAI. It accepts text and image inputs with text output, and is suited for agentic workflows, instruction-following tasks, and applications r
Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to del
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 SpaceXAI: Grok 4.3 (batch) to Reka Edge
Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to del Verified P90 latency of 280ms.