GLM 5.3 Flash (Fortanix) vs Gemma 4 31B

Practical read: GLM 5.3 Flash (Fortanix) costs under a tenth as much. Gemma 4 31B reads two times more context and starts answering sooner. One API key runs both.

No card required. Start with 1 million free tokens.

Side by side:

GLM 5.3 Flash (Fortanix) compared with Google: Gemma 4 31B
Attribute	GLM 5.3 Flash (Fortanix) `fortanix/glm-5.3-flash`	Gemma 4 31B `google/gemma-4-31b-it`
Price, 1M in + out	$0.02 Fortanix, cheapest route	$0.46 Weights & Biases, cheapest route
Best for	Low cost	Long documents and speed
Input / output, 1M	$0.01 / $0.01	$0.11 / $0.36
Cached input	Not published	$0.060927/1M to $0.26375/1M
Context window	131K 131,072 tokens	262K 262,144 tokens
First token, p50	1.4 s via Fortanix	0.63 s via Tinfoil
Throughput	Measuring	373 tok/s via FriendliAI
AI IQ	IQ 119 #50 on AI IQ	IQ 101 #120 on AI IQ
Provider routes	1	15 with failover
Privacy	Zero retention route	Confidential E2EE and zero retention route
Recent route uptime range	91.67%	0.00% to 100.00%
Publisher	fortanix	Google AI Studio
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 GLM 5.3 Flash (Fortanix) and Gemma 4 31B 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 fortanix/glm-5.3-flash, then on google/gemma-4-31b-it.
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 ("fortanix/glm-5.3-flash", "google/gemma-4-31b-it"):
    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 fortanix/glm-5.3-flash google/gemma-4-31b-it; 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, GLM 5.3 Flash (Fortanix) or Google: Gemma 4 31B?

GLM 5.3 Flash (Fortanix) has the lower published input-plus-output rate. Google: Gemma 4 31B has more Credits provider routes, the larger context window and the lower measured p50 time to first token.

Is GLM 5.3 Flash (Fortanix) or Google: Gemma 4 31B cheaper?

The current cheapest TrustedRouter route is $0.02/1M for GLM 5.3 Flash (Fortanix) and $0.4642/1M for Google: Gemma 4 31B. The comparison uses current catalog prices and updates as provider pricing changes.

Is GLM 5.3 Flash (Fortanix) or Google: Gemma 4 31B faster?

Current measured p50 time to first token is 1376 ms for GLM 5.3 Flash (Fortanix) and 629 ms for Google: Gemma 4 31B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test GLM 5.3 Flash (Fortanix) and Google: Gemma 4 31B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between fortanix/glm-5.3-flash and google/gemma-4-31b-it. This makes side-by-side evals possible without maintaining two provider integrations.

More comparisons

All comparisons

Try GLM 5.3 Flash (Fortanix) and Gemma 4 31B 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.