Fw Kimi K2.7 Code
Azure AI Foundry chatFw Kimi K2.7 Code is an Azure AI Foundry chat model.It supports a 262,144-token context windowwith up to 262,144 output tokens.Input is priced at $1.05/M tokens and output at $4.40/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route Fw Kimi K2.7 Code via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Fw Kimi K2.7 Code spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $1.05/M input · $4.40/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 | $1.05/M | |
| Output | $4.40/M | |
| Blended (3:1 in:out) | $1.89/M Cross-model comparable price | |
| Cached input | $0.210/M |
Context & limits
- Context window
- 262,144 tokens
- Max input
- 262,144 tokens
- Max output
- 262,144 tokens
- Modalities
- vision, text
Capabilities
- Function calling ✓ supported
- 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 ✓ supported
- Reasoning ✓ supported
Strengths & caveats — when to pick Fw Kimi K2.7 Code
Data-driven from Fw Kimi K2.7 Code's percentile within chat peers.
Where it's strong
- +long-form generation — 262,144-token max output, top-5% of peers
Watch out for
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmarks pending
We haven't logged public benchmark scores for Fw Kimi K2.7 Code yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Fw Kimi K2.7 Code 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.# Fw Kimi K2.7 Code 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="azure-ai-foundry/fw-kimi-k2-7-code",
messages=[{"role": "user", "content": "Hello, Fw Kimi K2.7 Code!"}],
)
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="azure-ai-foundry/fw-kimi-k2-7-code",
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
Fw Kimi K2.7 Code 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.
- GPT-5.4Azure AI Foundry · $2.50/M in · $15.00/M out · 922,000 ctxCompare side-by-side →
- GPT-5.5 (2026-04-23)Azure AI Foundry · $5.00/M in · $30.00/M out · 922,000 ctxCompare side-by-side →
- GPT-5.4 mini (2026-03-17)Azure AI Foundry · $0.750/M in · $4.50/M out · 272,000 ctxCompare side-by-side →
- Fw Kimi K2.6Azure AI Foundry · $1.05/M in · $4.40/M out · 262,144 ctxCompare side-by-side →
FAQ
How much does Fw Kimi K2.7 Code cost?
Input is priced at $1.05 per 1M tokens and output at $4.40 per 1M tokens (Azure AI Foundry, last verified Oct 22, 2026).
What is the context window of Fw Kimi K2.7 Code?
Fw Kimi K2.7 Code supports a 262,144-token context window with up to 262,144 output tokens.
Does Fw Kimi K2.7 Code support function calling?
Yes — Fw Kimi K2.7 Code supports function (tool) calling.
Is Fw Kimi K2.7 Code good for production?
Fw Kimi K2.7 Code is well-suited for long-form generation — 262,144-token max output, top-5% of peers. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.
How can I route to Fw Kimi K2.7 Code 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 Fw Kimi K2.7 Code
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.