Free Llama 4 API.
No key. No subscription.
Meta's Llama 4 Maverick (17B × 128 experts MoE), 131K context. No key, no wallet, no subscription. Just call it.
Try it now.
No API key. No wallet. No signup. Paste this into any terminal — the response streams back from Llama hosted free on NVIDIA, routed through BlockRun.
curl https://blockrun.ai/api/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "nvidia/llama-4-maverick",
"messages": [{"role": "user", "content": "Write a haiku about open-source models"}]
}'- Context
- 131K
- Price
- free
- Best for
- reasoning · coding
6 ways to use Llama free.
BlockRun is the access layer. Pick the surface that matches how you build — terminal, notebook, IDE, agent runtime — and the same free models work everywhere.
- python
# Works with the OpenAI SDK — no key required for free models from openai import OpenAI client = OpenAI( base_url="https://blockrun.ai/api/v1", api_key="not-needed-for-free-models", ) response = client.chat.completions.create( model="nvidia/llama-4-maverick", messages=[{"role": "user", "content": "Write a haiku about open-source models"}], ) print(response.choices[0].message.content) - shell
# Install Franklin curl -fsSL https://franklin.run/install | sh # Run with this model franklin chat --model nvidia/llama-4-maverick "Summarize the README" - shell
curl https://blockrun.ai/api/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "nvidia/llama-4-maverick", "messages": [{"role": "user", "content": "Write a haiku about open-source models"}] }' - 04
ClawRouter
smart router for OpenClaw / Claude Code — auto-picks free models when possible
Learn more →shell# Install once npm install -g @blockrun/clawrouter # Then point any OpenAI-compatible client at the local proxy. # ClawRouter routes to nvidia/llama-4-maverick (or the cheapest capable model) # without changing your code. - 05
Claude Code MCP
8 tools for Claude Code, Cursor & ChatGPT — call any free model from inside your editor
Learn more →shell# Add the BlockRun MCP server (Claude Code, Cursor, or ChatGPT desktop) claude mcp add blockrun --transport http https://mcp.blockrun.ai/mcp # Then call from inside the editor: # blockrun_chat(model="nvidia/llama-4-maverick", messages=[{role:"user", content:"…"}]) - typescript
// Works with the OpenAI SDK — no key required for free models import OpenAI from "openai"; const client = new OpenAI({ baseURL: "https://blockrun.ai/api/v1", apiKey: "not-needed-for-free-models", }); const r = await client.chat.completions.create({ model: "nvidia/llama-4-maverick", messages: [{ role: "user", content: "Write a haiku about open-source models" }], }); console.log(r.choices[0].message.content);
We don't share
your data.
Your prompt goes to the AI provider you picked. Nothing else, nowhere else. No training, no retention beyond the request, no profile linking.
- No training, no retention beyond the request. Your prompt is forwarded only to the AI provider you select.
- Wallet in, prompt out. Pseudonymous by default — no email, no phone number, no identity documents.
- Read the code, audit the wire format, run it yourself. @blockrun/llm and blockrun-llm on npm and PyPI.
Want Claude, GPT-5,
or Gemini too?
No subscription. No monthly minimum. Pay per call in USDC via x402 — works the same endpoint, same SDK, same model IDs. Connect a wallet, top up $5, call any frontier model. No credit card.
Everything you might
be wondering.
- Is the Llama 4 API really free?
- Yes. Meta's Llama 4 Maverick is hosted free on NVIDIA's build.nvidia.com tier and exposed through BlockRun without payment, signup, or wallet. We pass NVIDIA's quota straight through.
- Do I need an API key?
- No. The endpoint accepts unauthenticated requests when the model is free. For paid models (Claude, GPT-5, Gemini), you connect a wallet and pay per call via x402.
- What's the catch?
- NVIDIA's free tier may use prompts for service improvement — don't send PII or proprietary data. For private inference, route to paid models or run Llama yourself.
- What's the request size limit?
- 128 KB per request body for free models (vs 5 MB for paid). Plenty for most chat workloads but not for long context dumps.
- Can I use the OpenAI SDK?
- Yes. BlockRun is OpenAI-compatible — set base_url to https://blockrun.ai/api/v1 and any OpenAI client just works.