OpenAI compatible API · Attested · Public status

MoonshotAI: Kimi K2.6 vs Qwen 3.6 35B A3B

MoonshotAI: Kimi K2.6 vs Qwen 3.6 35B A3B: 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 K2.6 has more Credits provider routes and the larger context window. Qwen 3.6 35B A3B has the lower published input-plus-output rate. There is not enough recent probe data to compare speed.

$2.611442/1MMoonshotAI: Kimi K2.6 cheapest route

$1.1605/1MQwen 3.6 35B A3B cheapest route

1169 msMoonshotAI: Kimi K2.6 fastest measured p50 TTFT via sail-research

not enough dataQwen 3.6 35B A3B 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.

MoonshotAI: Kimi K2.6Qwen 3.6 35B A3B

Model idmoonshotai/kimi-k2.6qwen/qwen3-6-35b-a3b

Publisher Kimi Venice

AI IQ IQ 118#35 —

Context262,144 tokens256,000 tokens

Credits provider routes191

Cheapest route$2.611442/1M$1.1605/1M

Cached input$0.05275/1M to $0.38191/1MNot published

Privacy posturehas provider E2EE routeprovider posture varies

Fastest measured p50 TTFT1169 ms via sail-researchnot enough data

Highest measured throughput98 tok/s via azurenot enough data

Recent route uptime range87.50% to 100.00%not enough data

Modes chat chat

MoonshotAI: Kimi K2.6 routes

Overview19 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Qwen 3.6 35B A3B routes

Overview1 Credits routes

Related comparisons

Browse every comparison

MoonshotAI: Kimi K2.6 vs Z.ai: GLM 5.247 combined provider routes
MoonshotAI: Kimi K2.6 vs Z.ai: GLM 5.345 combined provider routes
DeepSeek: DeepSeek V4 Flash 0731 vs MoonshotAI: Kimi K2.644 combined provider routes
MoonshotAI: Kimi K2.6 vs Z.ai: GLM 5.3 Flash44 combined provider routes
MoonshotAI: Kimi K2.6 vs MoonshotAI: Kimi K343 combined provider routes
MoonshotAI: Kimi K2.6 vs OpenAI: gpt-oss-120b41 combined provider routes
DeepSeek: DeepSeek V4 Pro 0423 vs MoonshotAI: Kimi K2.636 combined provider routes
DeepSeek: DeepSeek V4 Flash 0423 vs MoonshotAI: Kimi K2.635 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="moonshotai/kimi-k2.6",
    messages=messages,
)

Questions

Which should I use, MoonshotAI: Kimi K2.6 or Qwen 3.6 35B A3B?

Is MoonshotAI: Kimi K2.6 or Qwen 3.6 35B A3B cheaper?

The current cheapest TrustedRouter route is $2.611442/1M for MoonshotAI: Kimi K2.6 and $1.1605/1M for Qwen 3.6 35B A3B. The comparison uses current catalog prices and updates as provider pricing changes.

Is MoonshotAI: Kimi K2.6 or Qwen 3.6 35B A3B faster?

Current measured p50 time to first token is 1169 ms for MoonshotAI: Kimi K2.6 and not enough data for Qwen 3.6 35B A3B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MoonshotAI: Kimi K2.6 and Qwen 3.6 35B A3B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between moonshotai/kimi-k2.6 and qwen/qwen3-6-35b-a3b. This makes side-by-side evals possible without maintaining two provider integrations.