MythoMax 13B vs Z.ai: GLM 4.6: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MythoMax 13B (gryphe/mythomax-l2-13b) vs Z.ai: GLM 4.6 (z-ai/glm-4.6). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MythoMax 13B (gryphe/mythomax-l2-13b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MythoMax 13B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.04/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 4.6 (z-ai/glm-4.6) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.6: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing MythoMax 13B (API ID: gryphe/mythomax-l2-13b) vs Z.ai: GLM 4.6 (API ID: z-ai/glm-4.6), MythoMax 13B offers lower standard input pricing at $0.08/1M tokens ($0.11/1M output), while MythoMax 13B leads in cached prefix economics at $0.04/1M tokens (50% discount). MythoMax 13B 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 | MythoMax 13B | Z.ai: GLM 4.6 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | gryphe/mythomax-l2-13b | z-ai/glm-4.6 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.08 / $0.11 | $0.5 / $2 | MythoMax 13B |
| Cache Read Price (per 1M) | $0.04/1M (50% Off) | $0.25/1M (50% Off) | MythoMax 13B |
| Context Window / Max Output | 8K In / 4K Out | 200K In / 128K Out | Z.ai: GLM 4.6 |
| P90 First-Token / Edge Latency | 280ms | 280ms | MythoMax 13B (-0ms) |
One of the highest performing and most popular fine-tunes of Llama 2 13B, with rich descriptions and roleplay. #merge
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to
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 MythoMax 13B to Z.ai: GLM 4.6
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to Verified P90 latency of 280ms.