meta-models/Muse-Glimmer-30B vs Kimi K3

Practical read: meta-models/Muse-Glimmer-30B costs about an eighth as much. Kimi K3 reads eight times more context. One API key runs both.

No card required. Start with 1 million free tokens.

Side by side:

meta-models/Muse-Glimmer-30B compared with MoonshotAI: Kimi K3
Attribute	meta-models/Muse-Glimmer-30B `meta-models/muse-glimmer-30b`	Kimi K3 `moonshotai/kimi-k3`
Price, 1M in + out	$1.58 DeepInfra, cheapest route	$11.97 Chutes, cheapest route
Best for	Low cost	Long documents
Input / output, 1M	$0.32 / $1.27	$1.95 / $10.02
Cached input	$0.0422/1M	$0.1688/1M to $1.046349/1M
Context window	131K 131,072 tokens	1.05M 1,048,576 tokens
AI IQ	Unrated	IQ 127 #22 on AI IQ
Provider routes	1	27 with failover
Privacy	Varies by provider	Confidential E2EE and zero retention route
Publisher	meta-models	Kimi
Modes	chat	chat
More detail	Overview	Overview Pricing Providers

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 meta-models/Muse-Glimmer-30B and Kimi K3 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 meta-models/muse-glimmer-30b, then on moonshotai/kimi-k3.
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 ("meta-models/muse-glimmer-30b", "moonshotai/kimi-k3"):
    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 meta-models/muse-glimmer-30b moonshotai/kimi-k3; 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

Your agent will need an API key.

Questions

Which should I use, meta-models/Muse-Glimmer-30B or MoonshotAI: Kimi K3?

meta-models/Muse-Glimmer-30B has the lower published input-plus-output rate. MoonshotAI: Kimi K3 has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

Is meta-models/Muse-Glimmer-30B or MoonshotAI: Kimi K3 cheaper?

The current cheapest TrustedRouter route is $1.5825/1M for meta-models/Muse-Glimmer-30B and $11.97425/1M for MoonshotAI: Kimi K3. The comparison uses current catalog prices and updates as provider pricing changes.

Can I test meta-models/Muse-Glimmer-30B and MoonshotAI: Kimi K3 with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-models/muse-glimmer-30b and moonshotai/kimi-k3. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try meta-models/Muse-Glimmer-30B and Kimi K3 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.