Ling 3.0 Flash vs GLM 5.3
Practical read: Ling 3.0 Flash costs about an eighth as much. GLM 5.3 reads eight times more context. One API key runs both.
No card required. Start with 1 million free tokens.
Side by side:
| Attribute | Ling 3.0 Flash | GLM 5.3 |
|---|---|---|
| Price, 1M in + out | $0.25 DeepInfra, cheapest route | $2.11 Pearl Research Labs, cheapest route |
| Best for | Low cost | Long documents |
| Input / output, 1M | $0.063 / $0.19 | $0.53 / $1.58 |
| Cached input | $0.01266/1M | $0.03165/1M to $0.96005/1M |
| Context window | 131K 131,072 tokens | 1.05M 1,048,576 tokens |
| First token, p50 | Measuring | 0.83 s via FriendliAI |
| Throughput | Measuring | 239 tok/s via Wafer |
| AI IQ | IQ 104 #105 on AI IQ | IQ 124 #30 on AI IQ |
| Provider routes | 2 with failover | 33 with failover |
| Privacy | Varies by provider | Confidential E2EE and zero retention route |
| Recent route uptime range | not enough data | 100.00% |
| Publisher | inclusionAI | 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 Ling 3.0 Flash and GLM 5.3 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 inclusionai/ling-3.0-flash, then on z-ai/glm-5.3.
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 ("inclusionai/ling-3.0-flash", "z-ai/glm-5.3"):
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 inclusionai/ling-3.0-flash z-ai/glm-5.3; 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?\"}]}"
doneQuestions
Which should I use, inclusionAI: Ling 3.0 Flash or Z.ai: GLM 5.3?
inclusionAI: Ling 3.0 Flash has the lower published input-plus-output rate. Z.ai: GLM 5.3 has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.
Is inclusionAI: Ling 3.0 Flash or Z.ai: GLM 5.3 cheaper?
The current cheapest TrustedRouter route is $0.2532/1M for inclusionAI: Ling 3.0 Flash and $2.11/1M for Z.ai: GLM 5.3. The comparison uses current catalog prices and updates as provider pricing changes.
Is inclusionAI: Ling 3.0 Flash or Z.ai: GLM 5.3 faster?
Current measured p50 time to first token is not enough data for inclusionAI: Ling 3.0 Flash and 826 ms for Z.ai: GLM 5.3. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.
Can I test inclusionAI: Ling 3.0 Flash and Z.ai: GLM 5.3 with the same API?
Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between inclusionai/ling-3.0-flash and z-ai/glm-5.3. This makes side-by-side evals possible without maintaining two provider integrations.
More comparisons
All comparisonsTry Ling 3.0 Flash and GLM 5.3 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.