Kimi K2.7 Code
Together AI chat Deprecated 69d agomodel fallback routing to swap models without code changes.
Kimi K2.7 Code is a Together AI chat model.It supports a 262,144-token context window.Input is priced at $0.950/M tokens and output at $4.00/M tokens. Route Kimi K2.7 Code via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Kimi K2.7 Code spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.9500/M input · $4.00/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 | $0.950/M | |
| Output | $4.00/M | |
| Blended (3:1 in:out) | $1.71/M Cross-model comparable price | |
| Cached input | $0.190/M |
Context & limits
- Context window
- 262,144 tokens
- Max input
- 262,144 tokens
- Max output
- —
- Modalities
- text
Capabilities
- Function calling — not advertised
- 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
Strengths & caveats — when to pick Kimi K2.7 Code
Data-driven from Kimi K2.7 Code's percentile within chat peers.
Where it's strong
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
- !already deprecated — provider stopped accepting new traffic 69 days ago
Benchmarks pending
We haven't logged public benchmark scores for Kimi K2.7 Code yet. Have one to contribute? Submit a source — citations help us prioritise.
Call 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.# 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="together-ai/moonshotai-kimi-k2-7-code",
messages=[{"role": "user", "content": "Hello, 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="together-ai/moonshotai-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 ↗Same model on other providers
moonshotai-kimi-k2-7-code is also available via 4 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| DeepInfra | $0.680/M | $3.40/M | Oct 22, 2026 |
| Novita AI | $0.950/M | $4.00/M | Oct 22, 2026 |
| Nebius | $0.950/M | $4.00/M | Oct 22, 2026 |
| W&B Inference | $0.710/M | $3.50/M | Oct 22, 2026 |
Explore similar models
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.
- Kimi K3Together AI · $3.00/M in · $15.00/M out · 1,048,576 ctxCompare side-by-side →
- GLM 5.3Together AI · $1.40/M in · $4.40/M out · 1,048,575 ctxCompare side-by-side →
- DeepSeek V4.1 Flash 1017Together AI · $0.300/M in · $1.20/M out · 1,048,576 ctxView model →
- GLM 5.3 FlashTogether AI · $0.150/M in · $0.500/M out · 1,048,575 ctxView model →
FAQ
How much does Kimi K2.7 Code cost?
Input is priced at $0.950 per 1M tokens and output at $4.00 per 1M tokens (Together AI, last verified Oct 22, 2026).
What is the context window of Kimi K2.7 Code?
Kimi K2.7 Code supports a 262,144-token context window.
Does Kimi K2.7 Code support function calling?
Kimi K2.7 Code 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 Kimi K2.7 Code good for production?
Kimi K2.7 Code is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.
How can I route to 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 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.