OpenAI compatible API · Attested · Public status

DeepSeek: DeepSeek V4 Flash 0731 vs Kimi K2.7 Code

DeepSeek V4 Flash 0731 vs 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

DeepSeek V4 Flash 0731 has the lower published input-plus-output rate, more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

$0.142425/1MDeepSeek: DeepSeek V4 Flash 0731 cheapest route
$4.48375/1MKimi K2.7 Code cheapest route
1259 msDeepSeek: DeepSeek V4 Flash 0731 fastest measured p50 TTFT via pearl
not enough dataKimi K2.7 Code fastest measured p50 TTFT

The price comparison adds each route's rate for one million input tokens and one million output tokens; your cost depends on your input/output mix. 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.

DeepSeek: DeepSeek V4 Flash 0731Kimi K2.7 Code
Model iddeepseek/deepseek-v4-flash-0731moonshotai/kimi-k2-7-code
AI IQ
Context1,048,576 tokens256,000 tokens
Credits provider routes241
Cheapest route$0.142425/1M$4.48375/1M
Cached input$0.01/1M to $0.101559/1M$0.1688/1M
Privacy posturehas confidential-compute routeprovider posture varies
Fastest measured p50 TTFT1259 ms via pearlnot enough data
Highest measured throughputnot enough datanot enough data
Recent route uptime range0.00% to 100.00%100.00%
Modes chat chat

DeepSeek: DeepSeek V4 Flash 0731 routes

Kimi K2.7 Code routes

Related comparisons

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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="deepseek/deepseek-v4-flash-0731",
    messages=messages,
)

Questions

Which should I use, DeepSeek: DeepSeek V4 Flash 0731 or Kimi K2.7 Code?

DeepSeek V4 Flash 0731 has the lower published input-plus-output rate, more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

Is DeepSeek: DeepSeek V4 Flash 0731 or Kimi K2.7 Code cheaper?

The current cheapest TrustedRouter route is $0.142425/1M for DeepSeek: DeepSeek V4 Flash 0731 and $4.48375/1M for Kimi K2.7 Code. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek: DeepSeek V4 Flash 0731 or Kimi K2.7 Code faster?

Current measured p50 time to first token is 1259 ms for DeepSeek: DeepSeek V4 Flash 0731 and not enough data for Kimi K2.7 Code. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test DeepSeek: DeepSeek V4 Flash 0731 and 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 deepseek/deepseek-v4-flash-0731 and moonshotai/kimi-k2-7-code. This makes side-by-side evals possible without maintaining two provider integrations.

Workspace access

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