Llama 3.1 405B Instruct Turbo
Together AI chatLlama 3.1 405B Instruct Turbo is a Together AI chat model.Input is priced at $3.50/M tokens and output at $3.50/M tokens. Capabilities include function calling. Route Llama 3.1 405B Instruct Turbo via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Llama 3.1 405B Instruct Turbo spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $3.50/M input · $3.50/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 Aug 6, 2026.
| Input | $3.50/M | |
| Output | $3.50/M | |
| Blended (3:1 in:out) | $3.50/M Cross-model comparable price |
Context & 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
Strengths & caveats — when to pick Llama 3.1 405B Instruct Turbo
Data-driven from Llama 3.1 405B Instruct Turbo's percentile within chat peers.
Where it's strong
- +parallel tool calls — only 18% 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 Llama 3.1 405B Instruct Turbo yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Llama 3.1 405B Instruct Turbo 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.# Llama 3.1 405B Instruct Turbo 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-meta-llama-3-1-405b-instruct-turbo",
messages=[{"role": "user", "content": "Hello, Llama 3.1 405B Instruct Turbo!"}],
)
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-meta-llama-3-1-405b-instruct-turbo",
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 ↗Explore similar models
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FAQ
How much does Llama 3.1 405B Instruct Turbo cost?
Input is priced at $3.50 per 1M tokens and output at $3.50 per 1M tokens (Together AI, last verified Aug 6, 2026).
What is the context window of Llama 3.1 405B Instruct Turbo?
Context window for Llama 3.1 405B Instruct Turbo is not currently public.
Does Llama 3.1 405B Instruct Turbo support function calling?
Yes — Llama 3.1 405B Instruct Turbo supports function (tool) calling, including parallel tool calls.
Is Llama 3.1 405B Instruct Turbo good for production?
Llama 3.1 405B Instruct Turbo is well-suited for parallel tool calls — only 18% of chat models on Future AGI advertise this.
How can I route to Llama 3.1 405B Instruct Turbo 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 Llama 3.1 405B Instruct Turbo
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.