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meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo vs GLM 5.2

Practical read: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo costs under a tenth as much. GLM 5.2 reads eight times more context. One API key runs both.

No card required. Start with 1 million free tokens.

Side by side:

meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo compared with Z.ai: GLM 5.2
Attribute meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo meta-llama/meta-llama-3.1-8b-instruct-turbo GLM 5.2 z-ai/glm-5.2
Price, 1M in + out $0.063 DeepInfra, cheapest route $2.30 Engy, cheapest route
Best for Low cost Long documents
Input / output, 1M $0.021 / $0.042 $0.72 / $1.58
Cached input Not published $0.131875/1M to $0.80391/1M
Context window 131K 131,072 tokens 1.05M 1,048,576 tokens
AI IQ Unrated IQ 118 #53 on AI IQ
Provider routes 1 32 with failover
Privacy Varies by provider Confidential E2EE and zero retention route
Publisher Meta Z.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 meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo and GLM 5.2 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-llama/meta-llama-3.1-8b-instruct-turbo, then on z-ai/glm-5.2.
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-llama/meta-llama-3.1-8b-instruct-turbo", "z-ai/glm-5.2"):
    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-llama/meta-llama-3.1-8b-instruct-turbo z-ai/glm-5.2; 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-llama/Meta-Llama-3.1-8B-Instruct-Turbo or Z.ai: GLM 5.2?

meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo has the lower published input-plus-output rate. Z.ai: GLM 5.2 has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

Is meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo or Z.ai: GLM 5.2 cheaper?

The current cheapest TrustedRouter route is $0.0633/1M for meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo and $2.2999/1M for Z.ai: GLM 5.2. The comparison uses current catalog prices and updates as provider pricing changes.

Can I test meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo and Z.ai: GLM 5.2 with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/meta-llama-3.1-8b-instruct-turbo and z-ai/glm-5.2. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo and GLM 5.2 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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