Meta Models Muse Spark Open 816B A42B

Together AI chat

Meta Models Muse Spark Open 816B A42B is a Together AI chat model.It supports a 1,048,576-token context window.Input is priced at $1.25/M tokens and output at $4.25/M tokens. Capabilities include function calling, prompt caching. Route Meta Models Muse Spark Open 816B A42B via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Oct 22, 2026 View source ↗
Cost calculator

Estimate Meta Models Muse Spark Open 816B A42B spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
01,048,576
400
016,000
5,000
01,000,000
cached @ $0.1500/M
Per request
$0.005450
in $0.003750 · out $0.001700
Per day
$27.25
5,000 requests
Per month
$829
152,188 requests

Estimate uses $1.25/M input · $4.25/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 Oct 22, 2026.

Input $1.25/M
Output $4.25/M
Blended (3:1 in:out) $2.00/M
Cross-model comparable price
Cached input $0.150/M

Context & limits

Context window
1,048,576 tokens
Max input
1,048,576 tokens
Max output
—
Modalities
text

Capabilities

  • Function calling ✓ supported
  • 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 ✓ supported
  • Reasoning — not advertised

Strengths & caveats — when to pick Meta Models Muse Spark Open 816B A42B

Data-driven from Meta Models Muse Spark Open 816B A42B's percentile within chat peers.

Where it's strong

  • +long-context tasks — context window in the top 2% of peers

Watch out for

  • No major caveats flagged from public spec.

Benchmarks pending

We haven't logged public benchmark scores for Meta Models Muse Spark Open 816B A42B yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Meta Models Muse Spark Open 816B A42B 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.

SDK
Native Future AGI client (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 Models Muse Spark Open 816B A42B 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-models-muse-spark-open-816b-a42b",
    messages=[{"role": "user", "content": "Hello, Meta Models Muse Spark Open 816B A42B!"}],
)

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-models-muse-spark-open-816b-a42b",
    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"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Explore similar models

Meta Models Muse Spark Open 816B A42B doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Meta Models Muse Spark Open 816B A42B cost?

Input is priced at $1.25 per 1M tokens and output at $4.25 per 1M tokens (Together AI, last verified Oct 22, 2026).

What is the context window of Meta Models Muse Spark Open 816B A42B?

Meta Models Muse Spark Open 816B A42B supports a 1,048,576-token context window.

Does Meta Models Muse Spark Open 816B A42B support function calling?

Yes — Meta Models Muse Spark Open 816B A42B supports function (tool) calling.

Is Meta Models Muse Spark Open 816B A42B good for production?

Meta Models Muse Spark Open 816B A42B is well-suited for long-context tasks — context window in the top 2% of peers.

How can I route to Meta Models Muse Spark Open 816B A42B 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 Models Muse Spark Open 816B A42B

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.