Kimi K3.1 Pro vs Qwen MT Lite
Practical read: Kimi K3.1 Pro reads eight times more context. Qwen MT Lite costs under a tenth as much. One API key runs both.
No card required. Start with 1 million free tokens.
Side by side:
| Attribute | Kimi K3.1 Pro | Qwen MT Lite |
|---|---|---|
| Price, 1M in + out | $8.86 Engy, cheapest route | $0.47 Alibaba Cloud Model Studio, cheapest route |
| Best for | Long documents | Low cost |
| Input / output, 1M | $1.48 / $7.38 | $0.053 / $0.42 |
| Cached input | $0.1477/1M to $0.422/1M | $0.01/1M |
| Context window | 1.05M 1,048,576 tokens | 131K 131,072 tokens |
| AI IQ | IQ 132 #14 on AI IQ | Unrated |
| Provider routes | 15 with failover | 1 |
| Privacy | Confidential E2EE and zero retention route | Varies by provider |
| Publisher | Kimi | Alibaba Cloud Model Studio |
| Modes | chat | chat |
| More detail |
Price adds one million input and one million output tokens on the cheapest route. Prices and speed change: see the monthly reports and run a small eval before you choose a default.
Test both with your agent
Paste this into Claude Code, Cursor or any coding agent.
Compare Kimi K3.1 Pro and Qwen MT Lite in this project through TrustedRouter.
1. Read https://trustedrouter.com/docs/llms.txt
2. Point the OpenAI-compatible client at
https://api-azure.trustedrouter.com/v1 and read the key from
TRUSTEDROUTER_API_KEY.
3. Run our eval prompts on moonshotai/kimi-k3.1-pro, then on qwen/qwen-mt-lite.
4. Show me cost, latency and quality side by side before changing the default.
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api-azure.trustedrouter.com/v1",
api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
for model in ("moonshotai/kimi-k3.1-pro", "qwen/qwen-mt-lite"):
response = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": "What is the capital of France?"}],
)
print(model, response.choices[0].message.content)
for model in moonshotai/kimi-k3.1-pro qwen/qwen-mt-lite; do
curl https://api-azure.trustedrouter.com/v1/chat/completions \
-H "Authorization: Bearer $TRUSTEDROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d "{\"model\": \"$model\", \"messages\": [{\"role\": \"user\", \"content\": \"What is the capital of France?\"}]}"
done
Questions
Which should I use, MoonshotAI: Kimi K3.1 Pro or Qwen MT Lite?
MoonshotAI: Kimi K3.1 Pro has more Credits provider routes and the larger context window. Qwen MT Lite has the lower published input-plus-output rate. There is not enough recent probe data to compare speed.
Is MoonshotAI: Kimi K3.1 Pro or Qwen MT Lite cheaper?
The current cheapest TrustedRouter route is $8.862/1M for MoonshotAI: Kimi K3.1 Pro and $0.47475/1M for Qwen MT Lite. The comparison uses current catalog prices and updates as provider pricing changes.
Can I test MoonshotAI: Kimi K3.1 Pro and Qwen MT Lite 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-k3.1-pro and qwen/qwen-mt-lite. This makes side-by-side evals possible without maintaining two provider integrations.
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Try Kimi K3.1 Pro and Qwen MT Lite with one key.
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.
No card required. Start with 1 million free tokens.