Kimi K2.0905 preview
Moonshot AI chatKimi K2.0905 preview is a Moonshot AI chat model.It supports a 262,144-token context windowwith up to 262,144 output tokens.Input is priced at $0.600/M tokens and output at $2.50/M tokens. Capabilities include function calling. Route Kimi K2.0905 preview via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Kimi K2.0905 preview spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.6000/M input · $2.50/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 May 12, 2026.
| Input | $0.600/M | |
| Output | $2.50/M | |
| Cached input | $0.150/M |
Limits
- Context window
- 262,144 tokens
- Max input
- 262,144 tokens
- Max output
- 262,144 tokens
- 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 — not advertised
Where it's strong
- +long-form generation — 262,144-token max output, top-1% of peers
Watch out for
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmark scores
Reported public benchmark numbers. Each row links to the source.
Call Kimi K2.0905 preview 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.# Kimi K2.0905 preview 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="moonshot/kimi-k2-0905-preview",
messages=[{"role": "user", "content": "Hello, Kimi K2.0905 preview!"}],
)
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="moonshot/kimi-k2-0905-preview",
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 ↗Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
- model: kimi-k2-0905-preview
provider: moonshot
weight: 80
fallbacks:
- model: deepseek-r1
provider: azure-ai-foundry
- model: gemini-2-5-flash
provider: vertex-ai
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }Compare with similar models
Grouped by Chatbot Arena tier (Kimi K2.0905 preview sits at 1330 ELO).
≥30 ELO higher
- Claude Opus 4.6Azure AI Foundry · $5.00/M in · $25.00/M out · 200,000 ctx
- Claude Opus 4.6 (2026-02-05)Anthropic · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Gemini 3.1 Pro previewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctx
- Claude Opus 4.7Azure AI Foundry · $5.00/M in · $25.00/M out · 200,000 ctx
25–100 ELO lower, ≤50% of price
FAQ
How much does Kimi K2.0905 preview cost?
Input is priced at $0.600 per 1M tokens and output at $2.50 per 1M tokens (Moonshot AI, last verified May 12, 2026).
What is the context window of Kimi K2.0905 preview?
Kimi K2.0905 preview supports a 262,144-token context window with up to 262,144 output tokens.
Does Kimi K2.0905 preview support function calling?
Yes — Kimi K2.0905 preview supports function (tool) calling.
Is Kimi K2.0905 preview good for production?
Kimi K2.0905 preview is well-suited for long-form generation — 262,144-token max output, top-1% of peers. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.
How can I route to Kimi K2.0905 preview 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 Kimi K2.0905 preview
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.