AllocateFLUX.1 Schnell vs Meta Llama 3.3 70B Instruct Turbo
FLUX.1 Schnell is not currently in the Allocate serving catalog, so this page lists no prices for it: every price on this site comes from the live catalog.
F FLUX.1 Schnell
Meta Llama 3.3 70B Instruct Turbo
Meta Llama 3.3 70B Instruct TurboLabBlack Forest LabsMeta
AccessNot served on AllocateOpen weights
Context windown/a128K tokens
List price, inputNot served$1.04 / M tokens
List price, outputNot served$1.04 / M tokens
Cached inputn/an/a
LicenseNot listedLlama community
Fine-tunableYesYes
Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.
Choose FLUX.1 Schnell for
- Draft and thumbnail generation
- High-volume image pipelines
- Open-weight image work
Choose Meta Llama 3.3 70B Instruct Turbo for
- Training toward a model you own
Common questions
Which has the bigger context window?
Meta Llama 3.3 70B Instruct Turbo: 131,072 tokens (128K) against an unlisted window for FLUX.1 Schnell.
Can I fine-tune FLUX.1 Schnell or Meta Llama 3.3 70B Instruct Turbo?
Both publish open weights (FLUX.1 Schnell: Not listed; Meta Llama 3.3 70B Instruct Turbo: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
FLUX.1 Schnell vs Llama 4 Scout Instruct (17Bx16E)Meta Llama 3.3 70B Instruct Turbo vs Llama 4 Scout Instruct (17Bx16E)FLUX.1 Schnell vs Meta Llama 3.1 405B InstructMeta Llama 3.3 70B Instruct Turbo vs Meta Llama 3.1 405B InstructFLUX.1 Schnell vs OpenAI GPT-OSS 120BMeta Llama 3.3 70B Instruct Turbo vs OpenAI GPT-OSS 120B
Run the numbers on your workload
Or do not 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.