Perplexity Kimi K3
Perplexity responsesPerplexity Kimi K3 is a Perplexity responses-API model.Input is priced at $3.00/M tokens and output at $15.00/M tokens. Capabilities include function calling, reasoning. Route Perplexity Kimi K3 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Perplexity Kimi K3 spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $3.00/M input · $15.00/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 | $3.00/M | |
| Output | $15.00/M | |
| Blended (3:1 in:out) | $6.00/M Cross-model comparable price | |
| Cached input | $0.300/M |
Context & limits
- Context window
- —
- Max input
- —
- 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 — not advertised
- Prompt caching — not advertised
- Reasoning ✓ supported
Strengths & caveats — when to pick Perplexity Kimi K3
Data-driven from Perplexity Kimi K3's percentile within responses peers.
Where it's strong
- +multi-step reasoning and analysis tasks
- +agentic workflows that depend on reliable tool calls
Watch out for
- No major caveats flagged from public spec.
Benchmarks pending
We haven't logged public benchmark scores for Perplexity Kimi K3 yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Perplexity Kimi K3 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.# Perplexity Kimi K3 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="perplexity/perplexity-kimi-k3",
messages=[{"role": "user", "content": "Hello, Perplexity Kimi K3!"}],
)
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="perplexity/perplexity-kimi-k3",
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 Perplexity Kimi K3 cost?
Input is priced at $3.00 per 1M tokens and output at $15.00 per 1M tokens (Perplexity, last verified Oct 22, 2026).
What is the context window of Perplexity Kimi K3?
Context window for Perplexity Kimi K3 is not currently public.
Does Perplexity Kimi K3 support function calling?
Yes — Perplexity Kimi K3 supports function (tool) calling.
Is Perplexity Kimi K3 good for production?
Perplexity Kimi K3 is well-suited for multi-step reasoning and analysis tasks and agentic workflows that depend on reliable tool calls.
How can I route to Perplexity Kimi K3 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 Perplexity Kimi K3
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.