MythoMax L2 13B
MythoMax L2 13B on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.
At a glance.
| Provider | Fireworks AI |
| Family | llama |
| Released | 2024-04 |
| License | Open weights |
| Context window | 4K tokens |
| Max output | 3K tokens |
| Parameters | 13B |
| Modalities | text |
| Tool calling | No |
| Reasoning mode | No |
| Caching | none |
| Batch discount | No batch tier |
What reuse looks like here.
Pricing, context, and capabilities for MythoMax L2 13B are live, but it is outside the flagship set Zumik benchmarks in depth, so measured reuse, capture, and warm TTFT are not shown yet. Run a workload estimate or route it by id to start collecting traces.
What you actually pay once caching works.
At a typical 55% prefix reuse, a million input tokens on MythoMax L2 13B effectively costs $0.09 instead of $0.09 - blending to roughly $0.09 with a 25% output share. There is no batch tier, so cost control here leans on caching and routing.
Estimate it for your workloadRoute it directly by id, or let an alias pick it when it wins under policy.
Same OpenAI client, this model.
from openai import OpenAI
client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")
r = client.responses.create(
model="mythomax-l2-13b",
input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached) # confirm reuseMythoMax L2 13B, answered.
How much does MythoMax L2 13B cost?
MythoMax L2 13B is $0.09 per million input tokens and $0.09 per million output tokens through Zumik. Cache reads are $0.09 per million, a 0% discount on input.
What is MythoMax L2 13B's context window?
MythoMax L2 13B supports a 4K-token context window with up to 3K output tokens.
Run MythoMax L2 13B with reuse measured.
Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.