Kimi K3.1 Pro vs Ternary Bonsai 27B

Practical read: Kimi K3.1 Pro reads four times more context and starts answering sooner. Ternary Bonsai 27B costs under a tenth as much. One API key runs both.

No card required. Start with 1 million free tokens.

Side by side:

MoonshotAI: Kimi K3.1 Pro compared with Ternary Bonsai 27B
Attribute	Kimi K3.1 Pro `moonshotai/kimi-k3.1-pro`	Ternary Bonsai 27B `prism-ml/ternary-bonsai-27b`
Price, 1M in + out	$8.86 Engy, cheapest route	$0.02 Together, cheapest route
Best for	Long documents and speed	Low cost
Input / output, 1M	$1.48 / $7.38	$0.01 / $0.01
Cached input	$0.1477/1M to $0.422/1M	Not published
Context window	1.05M 1,048,576 tokens	262K 262,144 tokens
First token, p50	0.94 s via Telnyx	1.3 s via Together
AI IQ	IQ 132 #14 on AI IQ	Unrated
Provider routes	15 with failover	1
Privacy	Confidential E2EE and zero retention route	Zero retention route
Recent route uptime range	100.00%	100.00%
Publisher	Kimi	prism-ml
Modes	chat	chat
More detail	Overview Pricing Providers	Overview

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 Ternary Bonsai 27B 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 prism-ml/ternary-bonsai-27b.
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", "prism-ml/ternary-bonsai-27b"):
    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 prism-ml/ternary-bonsai-27b; 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

Your agent will need an API key.

Questions

Which should I use, MoonshotAI: Kimi K3.1 Pro or Ternary Bonsai 27B?

MoonshotAI: Kimi K3.1 Pro has more Credits provider routes, the larger context window and the lower measured p50 time to first token. Ternary Bonsai 27B has the lower published input-plus-output rate.

Is MoonshotAI: Kimi K3.1 Pro or Ternary Bonsai 27B cheaper?

The current cheapest TrustedRouter route is $8.862/1M for MoonshotAI: Kimi K3.1 Pro and $0.02/1M for Ternary Bonsai 27B. The comparison uses current catalog prices and updates as provider pricing changes.

Is MoonshotAI: Kimi K3.1 Pro or Ternary Bonsai 27B faster?

Current measured p50 time to first token is 936 ms for MoonshotAI: Kimi K3.1 Pro and 1319 ms for Ternary Bonsai 27B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MoonshotAI: Kimi K3.1 Pro and Ternary Bonsai 27B 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 prism-ml/ternary-bonsai-27b. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try Kimi K3.1 Pro and Ternary Bonsai 27B 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.