Fireworks AI · none caching
Nous Capybara 7B V1.9
Nous Capybara 7B V1.9 on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.
Specifications
At a glance.
| Provider | Fireworks AI |
| Family | mistral |
| Released | — |
| License | Open weights |
| Context window | 33K tokens |
| Max output | — |
| Parameters | 7B |
| Modalities | text |
| Tool calling | No |
| Reasoning mode | No |
| Caching | none |
| Batch discount | No batch tier |
Measured by Zumik
What reuse looks like here.
Pricing, context, and capabilities for Nous Capybara 7B V1.9 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.
Call it
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="nous-capybara-7b-v1p9",
input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached) # confirm reuseFrequently asked
Nous Capybara 7B V1.9, answered.
How much does Nous Capybara 7B V1.9 cost?
Nous Capybara 7B V1.9 is an open-weights model routed through Fireworks AI. It is priced on the host's serverless size tier rather than a single published per-token list price, so it shows "—" here until profiled.
What is Nous Capybara 7B V1.9's context window?
Nous Capybara 7B V1.9 supports a 33K-token context window.
Does Nous Capybara 7B V1.9 support prompt caching?
Yes. Fireworks AI uses Automatic prompt caching (serverless and dedicated) caching. In the Zumik corpus, Nous Capybara 7B V1.9 shows a median cache capture of 75% on agent workloads.
Run Nous Capybara 7B V1.9 with reuse measured.
Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.