Fal AI Moondream3 preview Query

fal.ai chat

Fal AI Moondream3 preview Query is a fal.ai chat model.Input is priced at $0.400/M tokens and output at $3.50/M tokens. Capabilities include vision, reasoning. Route Fal AI Moondream3 preview Query 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 Fal AI Moondream3 preview Query spend

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

~3K in / ~400 out · 5K req/day
3,000
0200,000
400
016,000
5,000
01,000,000
Per request
$0.002600
in $0.001200 · out $0.001400
Per day
$13.00
5,000 requests
Per month
$396
152,188 requests

Estimate uses $0.4000/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 Oct 22, 2026.

Input $0.400/M
Output $3.50/M
Blended (3:1 in:out) $1.18/M
Cross-model comparable price

Context & limits

Context window
—
Max input
—
Max output
—
Modalities
vision, text

Capabilities

  • Function calling — not advertised
  • Parallel tool calls — not advertised
  • Vision input ✓ supported
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning ✓ supported

Strengths & caveats — when to pick Fal AI Moondream3 preview Query

Data-driven from Fal AI Moondream3 preview Query's percentile within chat peers.

Where it's strong

  • +multi-step reasoning and analysis tasks
  • +document, chart, and screenshot understanding

Watch out for

  • !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmarks pending

We haven't logged public benchmark scores for Fal AI Moondream3 preview Query yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Fal AI Moondream3 preview Query 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.
# Fal AI Moondream3 preview Query 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="fal-ai/fal-ai-moondream3-preview-query",
    messages=[{"role": "user", "content": "Hello, Fal AI Moondream3 preview Query!"}],
)

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="fal-ai/fal-ai-moondream3-preview-query",
    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 ↗

FAQ

How much does Fal AI Moondream3 preview Query cost?

Input is priced at $0.400 per 1M tokens and output at $3.50 per 1M tokens (fal.ai, last verified Oct 22, 2026).

What is the context window of Fal AI Moondream3 preview Query?

Context window for Fal AI Moondream3 preview Query is not currently public.

Does Fal AI Moondream3 preview Query support function calling?

Fal AI Moondream3 preview Query does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Fal AI Moondream3 preview Query good for production?

Fal AI Moondream3 preview Query is well-suited for multi-step reasoning and analysis tasks and document, chart, and screenshot understanding. Consider alternatives if you need agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback.

How can I route to Fal AI Moondream3 preview Query 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 Fal AI Moondream3 preview Query

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