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Models / Sao10K / Llama 3 8B Lunaris

Llama 3 8B Lunaris APIOPEN WEIGHTS8K context

by Sao10K · text->text · released 2024-08-13

Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3.

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.04
Output / 1M
$0.05
Context
8K
Providers
2
HF downloads · 30d
391
Cheaper than
99% of catalog

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Llama 3 8B Lunaris?

Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and general knowledge....

Llama 3 8B Lunaris on the release timeline

$0.05$0.39$3.00Llama 3 8B Lunaris · $0.052024-082024-122025-01
Each point is a llama release, placed at its launch date with its current output price (log scale, $/1M). Bubble size ∝ context window; Llama 3 8B Lunaris is highlighted. Source: provider catalog, verified July 2026.

Llama 3 8B Lunaris pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

ModelInput / 1MOutput / 1MCache readCache writeContext
Llama 3 8B Lunaris$0.04$0.058K

On output price, Llama 3 8B Lunaris is cheaper than 99% of the 309 models in the catalog. It is served by 2 providers; the best combined rate at our last snapshot was ≈ $0.04 / $0.05 per 1M via DeepInfra, with upstream quantizations fp8, bf16.

What Llama 3 8B Lunaris costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$2.20
RAG / knowledge base200M / 20M$9.00
Coding agent80M / 25M$4.45
Batch extraction150M / 8M$6.40
Content generation20M / 40M$2.80

Estimate your own monthly cost

= input × $0.04 + output × $0.05 per 1M · pay-as-you-go, computed in your browser.

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Llama 3 8B Lunaris vs alternatives

Pick Llama 3 8B Lunaris when you want open weights you can also self-host. If price is the only priority, Llama 3.1 8B Instruct is cheaper per token.
ModelInput / 1MOutput / 1MContextOur test
Llama 3 8B Lunaris$0.04$0.058K
Llama 3.3 Euryale 70B$0.65$0.75131K
Llama 3.1 Euryale 70B v2.2$0.85$0.85131K
Llama 3.1 70B Hanami x1$3.00$3.0016K
MythoMax 13B$0.06$0.064K
Llama 3.1 8B Instruct$0.02$0.03131K

When not to use Llama 3 8B Lunaris

Specs

Model IDsao10k/l3-lunaris-8b
Modalitytext->text (input: text)
Context window8,192 tokens
Max output16,384 tokens
Tool / function calling
Structured output (JSON)✅ Yes
Released2024-08-13
Knowledge cutoff2023-12-31
Open weightsSao10K/L3-8B-Lunaris-v1 · 391 downloads / 145 likes (30d)

How to call Llama 3 8B Lunaris

from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="sao10k/l3-lunaris-8b",
    messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)
curl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"sao10k/l3-lunaris-8b","messages":[{"role":"user","content":"Hello"}]}'
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "sao10k/l3-lunaris-8b",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Llama 3 8B Lunaris and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Llama 3 8B Lunaris

Tips are derived from Llama 3 8B Lunaris's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Llama 3 8B Lunaris

Popular open-source projects for running and building with Llama 3 8B Lunaris — star counts pulled from GitHub (July 2026).

ollama/ollama★ 175.3K
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Go
langgenius/dify★ 147.5K
Production-ready platform for agentic workflow development.
TypeScript
open-webui/open-webui★ 144.0K
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Python
langchain-ai/langchain★ 140.8K
The agent engineering platform.
Python
ggml-org/llama.cpp★ 119.1K
LLM inference in C/C++
C++
vllm-project/vllm★ 85.2K
A high-throughput and memory-efficient inference and serving engine for LLMs
Python

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Llama 3 8B Lunaris

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → sao10k/l3-lunaris-8b. Messages, streaming and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Llama 3 8B Lunaris ships open weights (Sao10K/L3-8B-Lunaris-v1, ~391 downloads and 145 likes in the last 30 days), with community quantizations (fp8, bf16) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 2 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff; because Llama 3 8B Lunaris is served by 2 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

How OpenAI-Compatible APIs Work
DataLLM Lab Blog
We Benchmarked LLM Coding Cost & Quality
DataLLM Lab Blog
Best LLM API in 2026: A Buyer’s Guide
DataLLM Lab Blog

Call Llama 3 8B Lunaris with one key

300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.

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Frequently asked questions

What is Llama 3 8B Lunaris?

Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It accepts text input with a 8K-token context window and was released on 2024-08-13. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Llama 3 8B Lunaris cost?

On DataLLM Lab it is $0.04 per 1M input tokens and $0.05 per 1M output tokens — cheaper than about 99% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Llama 3 8B Lunaris?

8K tokens, with up to 16K max output tokens.

Is Llama 3 8B Lunaris open source?

Yes — open weights are published on Hugging Face (Sao10K/L3-8B-Lunaris-v1), with about 391 downloads and 145 likes in the last 30 days. You can self-host it or call it via DataLLM Lab.

How do I call the Llama 3 8B Lunaris API?

Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "sao10k/l3-lunaris-8b". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.

What are good alternatives to Llama 3 8B Lunaris?

Close options by price and capability include Llama 3.3 Euryale 70B, Llama 3.1 Euryale 70B v2.2, Llama 3.1 70B Hanami x1 — all callable with the same DataLLM Lab key.