@cf/mistralai/mistral-small-3.1-24b-instruct vs GLM 5.2
Practical read: @cf/mistralai/mistral-small-3.1-24b-instruct costs about half 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:
| Attribute | @cf/mistralai/mistral-small-3.1-24b-instruct | GLM 5.2 |
|---|---|---|
| Price, 1M in + out | $0.96 Cloudflare Workers AI, cheapest route | $2.30 Engy, cheapest route |
| Best for | Low cost | Long documents |
| Input / output, 1M | $0.37 / $0.59 | $0.72 / $1.58 |
| Cached input | Not published | $0.131875/1M to $0.773315/1M |
| Context window | 128K 128,000 tokens | 1.05M 1,048,576 tokens |
| First token, p50 | Measuring | 0.66 s via FriendliAI |
| Throughput | Measuring | 265 tok/s via Telnyx |
| AI IQ | Unrated | IQ 118 #53 on AI IQ |
| Provider routes | 1 | 31 with failover |
| Privacy | Varies by provider | Confidential E2EE and zero retention route |
| Recent route uptime range | 100.00% | 0.00% to 100.00% |
| Publisher | Mistral | 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 @cf/mistralai/mistral-small-3.1-24b-instruct 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.trustedrouter.com/v1 and read the key from
TRUSTEDROUTER_API_KEY.
3. Run our eval prompts on mistralai/mistral-small-3.1-24b-instruct, 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.trustedrouter.com/v1",
api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
for model in ("mistralai/mistral-small-3.1-24b-instruct", "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 mistralai/mistral-small-3.1-24b-instruct z-ai/glm-5.2; 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, @cf/mistralai/mistral-small-3.1-24b-instruct or Z.ai: GLM 5.2?
@cf/mistralai/mistral-small-3.1-24b-instruct 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 @cf/mistralai/mistral-small-3.1-24b-instruct or Z.ai: GLM 5.2 cheaper?
The current cheapest TrustedRouter route is $0.95583/1M for @cf/mistralai/mistral-small-3.1-24b-instruct and $2.2999/1M for Z.ai: GLM 5.2. The comparison uses current catalog prices and updates as provider pricing changes.
Is @cf/mistralai/mistral-small-3.1-24b-instruct or Z.ai: GLM 5.2 faster?
Current measured p50 time to first token is not enough data for @cf/mistralai/mistral-small-3.1-24b-instruct and 659 ms for Z.ai: GLM 5.2. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.
Can I test @cf/mistralai/mistral-small-3.1-24b-instruct 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 mistralai/mistral-small-3.1-24b-instruct and z-ai/glm-5.2. This makes side-by-side evals possible without maintaining two provider integrations.
More comparisons
All comparisonsTry @cf/mistralai/mistral-small-3.1-24b-instruct 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.