Meta Llama Llama 3.3 70B Instruct Turbo Free
Together AI chatMeta Llama Llama 3.3 70B Instruct Turbo Free is a Together AI chat model. Capabilities include function calling. Route Meta Llama Llama 3.3 70B Instruct Turbo Free via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
We don't have verified per-token pricing for Meta Llama Llama 3.3 70B Instruct Turbo Free yet. If you have a source from Together AI's documentation, help us add it — your submission gets reviewed within 48 hours.
Pricing
Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.
| Input | — | |
| Output | — |
Limits
- Context window
- —
- Max input
- —
- Max output
- —
- Modalities
- text
Capabilities
- Function calling ✓ supported
- Parallel tool calls ✓ supported
- 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
- +parallel tool calls — only 21% of chat models on Future AGI advertise this
Watch out for
- No major caveats flagged from public spec.
Benchmarks pending
We haven't logged public benchmark scores for Meta Llama Llama 3.3 70B Instruct Turbo Free yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Meta Llama Llama 3.3 70B Instruct Turbo Free 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.# Meta Llama Llama 3.3 70B Instruct Turbo Free 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="together-ai/meta-llama-llama-3-3-70b-instruct-turbo-free",
messages=[{"role": "user", "content": "Hello, Meta Llama Llama 3.3 70B Instruct Turbo Free!"}],
)
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="together-ai/meta-llama-llama-3-3-70b-instruct-turbo-free",
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
Meta Llama Llama 3.3 70B Instruct Turbo Free doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.
FAQ
How much does Meta Llama Llama 3.3 70B Instruct Turbo Free cost?
Public per-token pricing for Meta Llama Llama 3.3 70B Instruct Turbo Free is not yet published. Submit a source on this page to help us add it.
What is the context window of Meta Llama Llama 3.3 70B Instruct Turbo Free?
Context window for Meta Llama Llama 3.3 70B Instruct Turbo Free is not currently public.
Does Meta Llama Llama 3.3 70B Instruct Turbo Free support function calling?
Yes — Meta Llama Llama 3.3 70B Instruct Turbo Free supports function (tool) calling, including parallel tool calls.
Is Meta Llama Llama 3.3 70B Instruct Turbo Free good for production?
Meta Llama Llama 3.3 70B Instruct Turbo Free is well-suited for parallel tool calls — only 21% of chat models on Future AGI advertise this.
How can I route to Meta Llama Llama 3.3 70B Instruct Turbo Free 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 Meta Llama Llama 3.3 70B Instruct Turbo Free
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.