Comparisons /

Meta Llama 3 70B Instruct Turbo vs Muse Glimmer 30B

On provider list prices, Meta Llama 3 70B Instruct Turbo costs $0.88 per million input tokens against $0.35 for Muse Glimmer 30B: effectively level. Output is $0.88 against $1.50 (1.7x).

Meta Llama 3 70B Instruct Turbo Muse Glimmer 30B
LabMetaMeta
AccessOpen weightsOpen weights
Context window8K tokens128K tokens
List price, input$0.88 / M tokens$0.35 / M tokens
List price, output$0.88 / M tokens$1.5 / M tokens
Cached inputn/a$0.04 / M tokens
LicenseLlama communityNot listed
Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.

What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $945 a month on Muse Glimmer 30B and $1,364 on Meta Llama 3 70B Instruct Turbo at list: a gap of $419, or 1.4x.

Muse Glimmer 30B reads 128K tokens per request against 8K for Meta Llama 3 70B Instruct Turbo, 16.0x the window. That decides which one can take whole documents without splitting them.

Muse Glimmer 30B$0.35$1.50
Meta Llama 3 70B Instruct Turbo$0.88$0.88
InputOutput

Choose Meta Llama 3 70B Instruct Turbo for

  • Training toward a model you own
Meta Llama 3 70B Instruct Turbo details →

Choose Muse Glimmer 30B for

  • The lower list price ($0.35 in / $1.50 out per M tokens)
  • The longer context window (128K vs 8K tokens)
  • Published cached-input pricing ($0.04 per M tokens)
Muse Glimmer 30B details →

Common questions

Which is cheaper, Meta Llama 3 70B Instruct Turbo or Muse Glimmer 30B?

Muse Glimmer 30B, on this workload shape. At list prices it is $0.35/$1.50 per million tokens in and out against $0.88/$0.88 for Meta Llama 3 70B Instruct Turbo. Billed on Allocate: $0.37/$1.60 against $0.94/$0.94.

Which has the bigger context window?

Muse Glimmer 30B: 131,072 tokens (128K) against 8,192 (8K) for Meta Llama 3 70B Instruct Turbo.

Can I fine-tune Meta Llama 3 70B Instruct Turbo or Muse Glimmer 30B?

Both publish open weights (Meta Llama 3 70B Instruct Turbo: Llama community; Muse Glimmer 30B: 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 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.