Sao10k L3.8b Lunaris
Novita AI chatSao10k L3.8b Lunaris is a Novita AI chat model.It supports a 8,192-token context windowwith up to 8,192 output tokens.Input is priced at $0.0500/M tokens and output at $0.0500/M tokens. Route Sao10k L3.8b Lunaris via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Sao10k L3.8b Lunaris spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.0500/M input · $0.0500/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.
Pricing
Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.
| Input | $0.0500/M | |
| Output | $0.0500/M |
Limits
- Context window
- 8,192 tokens
- Max input
- 8,192 tokens
- Max output
- 8,192 tokens
- Modalities
- text
Capabilities
- Function calling — not advertised
- Parallel tool calls — not advertised
- Vision input — not advertised
- Audio input — not advertised
- Audio output — not advertised
- PDF input — not advertised
- Streaming ✓ supported
- Structured output ✓ supported
- Prompt caching — not advertised
- Reasoning — not advertised
Where it's strong
Watch out for
- !high cost — input + output rates are in the top 98% of priced chat peers; consider a cheaper sibling for high-volume workloads
- !limited context — 8,192-token window is in the bottom quartile; not ideal for long documents or large RAG
- !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
- !small context (under 16K tokens)
Benchmarks pending
We haven't logged public benchmark scores for Sao10k L3.8b Lunaris yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Sao10k L3.8b Lunaris via Agent Command Center
One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.
agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.# Sao10k L3.8b Lunaris via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC
client = AgentCC(
api_key=os.environ["AGENTCC_API_KEY"], # from app.futureagi.com → Settings → API Keys
base_url="https://gateway.futureagi.com/v1",
)
resp = client.chat.completions.create(
model="novita-ai/sao10k-l3-8b-lunaris",
messages=[{"role": "user", "content": "Hello, Sao10k L3.8b Lunaris!"}],
)
print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")
# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
model="novita-ai/sao10k-l3-8b-lunaris",
messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost: ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache: ", raw.headers.get("x-agentcc-cache"))AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗Compare with similar models
Sao10k L3.8b Lunaris doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.
- Baidu Ernie 4.5 VL 28B A3b ThinkingNovita AI · $0.390/M in · $0.390/M out · 131,072 ctx
- OpenAI GPT Oss 120BNovita AI · $0.0500/M in · $0.250/M out · 131,072 ctx
- Zai Org Glm 4.6vNovita AI · $0.300/M in · $0.900/M out · 131,072 ctx
- Qwen Qwen3 Omni 30B A3b ThinkingNovita AI · $0.250/M in · $0.970/M out · 65,536 ctx
FAQ
How much does Sao10k L3.8b Lunaris cost?
Input is priced at $0.0500 per 1M tokens and output at $0.0500 per 1M tokens (Novita AI, last verified May 12, 2026).
What is the context window of Sao10k L3.8b Lunaris?
Sao10k L3.8b Lunaris supports a 8,192-token context window with up to 8,192 output tokens.
Does Sao10k L3.8b Lunaris support function calling?
Sao10k L3.8b Lunaris does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.
Is Sao10k L3.8b Lunaris good for production?
Sao10k L3.8b Lunaris is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.
How can I route to Sao10k L3.8b Lunaris with fallback?
Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.
Useful links for Sao10k L3.8b Lunaris
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.