OpenAI compatible API · Attested · Public status

cohere-command-a vs MoonshotAI: Kimi K2.7 Code

cohere-command-a vs MoonshotAI: Kimi K2.7 Code: compare current API pricing, context, provider routes, privacy, p50 latency, and OpenAI-compatible access.

Verify gateway

Onebase URL to migrate

100sof models and routes

0prompt or output logs. Always.

Compare routesProviders, price, context, and policy posture in one view.

Use auto when uptime mattersKeep a primary model and let fallback handle provider failures.

Same API shapeUse the OpenAI client and set the model you want.

Practical read

Monthly evidence

MoonshotAI: Kimi K2.7 Code has the lower cheapest prompt+completion route on TrustedRouter. MoonshotAI: Kimi K2.7 Code has more provider fallback routes, while MoonshotAI: Kimi K2.7 Code has the larger context window. Current TrustedRouter probes show cohere-command-a with the lower p50 TTFT.

$13.1875/1Mcohere-command-a cheapest route

$4.29385/1MMoonshotAI: Kimi K2.7 Code cheapest route

1109 mscohere-command-a fastest measured p50 TTFT via azure

1203 msMoonshotAI: Kimi K2.7 Code fastest measured p50 TTFT via fireworks

Prices and live route measurements can change. Use the monthly reports when you need a stable evidence window, then run a small task-specific eval before choosing a production default.

cohere-command-aMoonshotAI: Kimi K2.7 Code

Model idcohere/command-amoonshotai/kimi-k2.7-code

Publisher Microsoft Azure AI Foundry Kimi

AI IQ — IQ 108#66

Context0 tokens262,144 tokens

Credits provider routes113

Cheapest route$13.1875/1M$4.29385/1M

Cached inputNot published$0.15825/1M to $0.465255/1M

Privacy postureprovider posture varieshas ZDR route

Fastest measured p50 TTFT1109 ms via azure1203 ms via fireworks

Highest measured throughputnot enough datanot enough data

Recent route uptime range100.00%100.00%

Modes chat chat

cohere-command-a routes

Overview1 Credits routes

MoonshotAI: Kimi K2.7 Code routes

Overview13 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Related comparisons

Browse every comparison

MoonshotAI: Kimi K2.7 Code vs Z.ai: GLM 5.241 combined provider routes
MoonshotAI: Kimi K2.7 Code vs Z.ai: GLM 5.339 combined provider routes
MoonshotAI: Kimi K2.7 Code vs Z.ai: GLM 5.3 Flash39 combined provider routes
DeepSeek: DeepSeek V4 Flash 0731 vs MoonshotAI: Kimi K2.7 Code37 combined provider routes
MoonshotAI: Kimi K2.7 Code vs MoonshotAI: Kimi K337 combined provider routes
MoonshotAI: Kimi K2.7 Code vs OpenAI: gpt-oss-120b35 combined provider routes
MoonshotAI: Kimi K2.6 vs MoonshotAI: Kimi K2.7 Code33 combined provider routes
DeepSeek: DeepSeek V4 Flash 0423 vs MoonshotAI: Kimi K2.7 Code30 combined provider routes

Production choice

Pick a default model. Keep fallback enabled.

TrustedRouter is useful when you know the model you want, but still need provider rollover, budget limits, usage records, and a prompt path you can verify.

OpenAI clientPython

client = OpenAI(
    base_url="https://api.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="cohere/command-a",
    messages=messages,
)

Questions

Which should I use, cohere-command-a or MoonshotAI: Kimi K2.7 Code?

Is cohere-command-a or MoonshotAI: Kimi K2.7 Code cheaper?

The current cheapest TrustedRouter route is $13.1875/1M for cohere-command-a and $4.29385/1M for MoonshotAI: Kimi K2.7 Code. The comparison uses current catalog prices and updates as provider pricing changes.

Is cohere-command-a or MoonshotAI: Kimi K2.7 Code faster?

Current measured p50 time to first token is 1109 ms for cohere-command-a and 1203 ms for MoonshotAI: Kimi K2.7 Code. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test cohere-command-a and MoonshotAI: Kimi K2.7 Code with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between cohere/command-a and moonshotai/kimi-k2.7-code. This makes side-by-side evals possible without maintaining two provider integrations.