Llama Guard 4 12B vs Qwen3.5 9B FP8
On provider list prices, Llama Guard 4 12B costs $0.20 per million input tokens against $0.17 for Qwen3.5 9B FP8: effectively level. Output is $0.20 against $0.25 (1.3x). On Allocate both bill at list plus the 7% transaction fee.
Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $291.50 a month on Qwen3.5 9B FP8 and $310 on Llama Guard 4 12B at list: a gap of $18.50.
Llama Guard 4 12B reads 1M tokens per request against 256K for Qwen3.5 9B FP8, 4.0x the window. That decides which one can take whole documents without splitting them.
Choose Qwen3.5 9B FP8 for
- The lower list price ($0.17 in / $0.25 out per M tokens)
Common questions
Which is cheaper, Llama Guard 4 12B or Qwen3.5 9B FP8?
Qwen3.5 9B FP8, on this workload shape. At list prices it is $0.17/$0.25 per million tokens in and out against $0.20/$0.20 for Llama Guard 4 12B. Billed on Allocate: $0.18/$0.27 against $0.21/$0.21, list plus 7%.
Which has the bigger context window?
Llama Guard 4 12B: 1,048,576 tokens (1M) against 262,144 (256K) for Qwen3.5 9B FP8.
Can I fine-tune Llama Guard 4 12B or Qwen3.5 9B FP8?
Both publish open weights (Llama Guard 4 12B: Llama community; Qwen3.5 9B FP8: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
Run the numbers on your workload
Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.