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Kimi K2.6 vs @cf/nvidia/nemotron-3-120b-a12b

Try both on us. Starter credit covers your first requests, then one key routes Kimi K2.6 and @cf/nvidia/nemotron-3-120b-a12b. Switch by changing the model name.

No card required. Start with 1 million free tokens.

Side by side:

MoonshotAI: Kimi K2.6 compared with @cf/nvidia/nemotron-3-120b-a12b
Attribute Kimi K2.6 moonshotai/kimi-k2.6 @cf/nvidia/nemotron-3-120b-a12b nvidia/nemotron-3-120b-a12b
Price, 1M in + out $2.31 Chutes, cheapest route $2.11 Cloudflare Workers AI, cheapest route
Input / output, 1M $0.41 / $1.90 $0.53 / $1.58
Cached input $0.041145/1M to $0.427223/1M Not published
Context window 262K 262,144 tokens 256K 256,000 tokens
First token, p50 1.4 s via Kimi Measuring
AI IQ IQ 114 #62 on AI IQ Unrated
Provider routes 16 with failover 1
Privacy Confidential E2EE and zero retention route Varies by provider
Recent route uptime range 100.00% not enough data
Publisher Kimi NVIDIA
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 K2.6 and @cf/nvidia/nemotron-3-120b-a12b 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-k2.6, then on nvidia/nemotron-3-120b-a12b.
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-k2.6", "nvidia/nemotron-3-120b-a12b"):
    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-k2.6 nvidia/nemotron-3-120b-a12b; 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 K2.6 or @cf/nvidia/nemotron-3-120b-a12b?

MoonshotAI: Kimi K2.6 has more Credits provider routes and the larger context window. @cf/nvidia/nemotron-3-120b-a12b has the lower published input-plus-output rate. There is not enough recent probe data to compare speed.

Is MoonshotAI: Kimi K2.6 or @cf/nvidia/nemotron-3-120b-a12b cheaper?

The current cheapest TrustedRouter route is $2.31045/1M for MoonshotAI: Kimi K2.6 and $2.11/1M for @cf/nvidia/nemotron-3-120b-a12b. The comparison uses current catalog prices and updates as provider pricing changes.

Is MoonshotAI: Kimi K2.6 or @cf/nvidia/nemotron-3-120b-a12b faster?

Current measured p50 time to first token is 1416 ms for MoonshotAI: Kimi K2.6 and not enough data for @cf/nvidia/nemotron-3-120b-a12b. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MoonshotAI: Kimi K2.6 and @cf/nvidia/nemotron-3-120b-a12b 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 nvidia/nemotron-3-120b-a12b. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try Kimi K2.6 and @cf/nvidia/nemotron-3-120b-a12b 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.

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