Kimi K3.1 Pro vs Document Structured Extraction
Practical read: Kimi K3.1 Pro reads more context and starts answering sooner. Document Structured Extraction 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 | Document Structured Extraction |
|---|---|---|
| Price, 1M in + out | $8.86 Engy, cheapest route | $0.12 Neurometric AI, cheapest route |
| Best for | Long documents and speed | Low cost |
| Input / output, 1M | $1.48 / $7.38 | $0.011 / $0.11 |
| Cached input | $0.1477/1M to $0.422/1M | Not published |
| Context window | 1.05M 1,048,576 tokens | 49K 49,152 tokens |
| First token, p50 | 0.94 s via Telnyx | 1.2 s via Neurometric AI |
| 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 |
| Recent route uptime range | 100.00% | 100.00% |
| Publisher | Kimi | Neurometric AI |
| 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 Document Structured Extraction in this project through TrustedRouter.
1. Read https://trustedrouter.com/docs/llms.txt
2. Point the OpenAI-compatible client at
https://api.trustedrouter.com/v1 and read the key from
TRUSTEDROUTER_API_KEY.
3. Run our eval prompts on moonshotai/kimi-k3.1-pro, then on neurometric/document-structured-extraction.
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.trustedrouter.com/v1",
api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
for model in ("moonshotai/kimi-k3.1-pro", "neurometric/document-structured-extraction"):
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 neurometric/document-structured-extraction; do
curl https://api.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 Document Structured Extraction?
MoonshotAI: Kimi K3.1 Pro has more Credits provider routes, the larger context window and the lower measured p50 time to first token. Document Structured Extraction has the lower published input-plus-output rate.
Is MoonshotAI: Kimi K3.1 Pro or Document Structured Extraction cheaper?
The current cheapest TrustedRouter route is $8.862/1M for MoonshotAI: Kimi K3.1 Pro and $0.11605/1M for Document Structured Extraction. The comparison uses current catalog prices and updates as provider pricing changes.
Is MoonshotAI: Kimi K3.1 Pro or Document Structured Extraction faster?
Current measured p50 time to first token is 936 ms for MoonshotAI: Kimi K3.1 Pro and 1246 ms for Document Structured Extraction. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.
Can I test MoonshotAI: Kimi K3.1 Pro and Document Structured Extraction 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 neurometric/document-structured-extraction. This makes side-by-side evals possible without maintaining two provider integrations.
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Try Kimi K3.1 Pro and Document Structured Extraction 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.