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DeepSeek V4 vs Meta Llama 3.3 70B Instruct Turbo

On provider list prices, Meta Llama 3.3 70B Instruct Turbo costs $1.04 per million input tokens against $1.74 for DeepSeek V4: 1.7x apart. Output is $1.04 against $3.48 (3.3x). On Allocate both bill at list plus the 7% transaction fee.

DeepSeek V4 Meta Llama 3.3 70B Instruct Turbo
LabDeepseekMeta
AccessAPI onlyOpen weights
Context window512K tokens128K tokens
List price, input$1.74 / M tokens$1.04 / M tokens
List price, output$3.48 / M tokens$1.04 / M tokens
Cached input$0.2 / M tokensn/a
LicenseProprietary APILlama community
Fine-tunableNoYes

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 $1,612 a month on Meta Llama 3.3 70B Instruct Turbo and $3,306 on DeepSeek V4 at list: a gap of $1,694, or 2.1x.

DeepSeek V4 reads 512K tokens per request against 128K for Meta Llama 3.3 70B Instruct Turbo, 3.9x the window. That decides which one can take whole documents without splitting them.

Meta Llama 3.3 70B Instruct Turbo$1.04$1.04
DeepSeek V4$1.74$3.48
InputOutput

Choose DeepSeek V4 for

  • Reasoning-heavy agents
  • Long-document analysis
  • Cost-sensitive production routes
DeepSeek V4 details

Choose Meta Llama 3.3 70B Instruct Turbo for

  • The lower list price ($1.04 in / $1.04 out per M tokens)
  • Open weights you can fine-tune and own
Meta Llama 3.3 70B Instruct Turbo details

Common questions

Which is cheaper, DeepSeek V4 or Meta Llama 3.3 70B Instruct Turbo?

Meta Llama 3.3 70B Instruct Turbo, on this workload shape. At list prices it is $1.04/$1.04 per million tokens in and out against $1.74/$3.48 for DeepSeek V4. Billed on Allocate: $1.11/$1.11 against $1.86/$3.72, list plus 7%.

Which has the bigger context window?

DeepSeek V4: 512,000 tokens (512K) against 131,072 (128K) for Meta Llama 3.3 70B Instruct Turbo.

Can I fine-tune DeepSeek V4 or Meta Llama 3.3 70B Instruct Turbo?

Meta Llama 3.3 70B Instruct Turbo publishes open weights (Llama community) and can be fine-tuned on your own data. DeepSeek V4 is a closed model served over API; its weights are not available.

Related comparisons

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Run the numbers on your workload

LLM price comparisonAgent cost calculatorDeepSeek V4Meta Llama 3.3 70B Instruct Turbo

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.

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