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Comparisons

DeepSeek V4 Flash vs Meta Llama 3 8B Instruct Reference

On provider list prices, Meta Llama 3 8B Instruct Reference costs $0.20 per million input tokens against $0.14 for DeepSeek V4 Flash: effectively level. Output is $0.20 against $0.28 (1.4x).

DeepSeek V4 Flash Meta Llama 3 8B Instruct Reference
LabDeepseekMeta
AccessOpen weightsOpen weights
Context window1M tokens8K tokens
List price, input$0.14 / M tokens$0.2 / M tokens
List price, output$0.28 / M tokens$0.2 / M tokens
Cached input$0.028 / M tokensn/a
LicenseNot listedLlama community
Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.

What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $266 a month on DeepSeek V4 Flash and $310 on Meta Llama 3 8B Instruct Reference at list: a gap of $44.00, or 1.2x.

DeepSeek V4 Flash reads 1M tokens per request against 8K for Meta Llama 3 8B Instruct Reference, 128.0x the window. That decides which one can take whole documents without splitting them.

DeepSeek V4 Flash$0.14$0.28
Meta Llama 3 8B Instruct Reference$0.20$0.20
InputOutput

Choose DeepSeek V4 Flash for

  • The lower list price ($0.14 in / $0.28 out per M tokens)
  • The longer context window (1M vs 8K tokens)
  • Published cached-input pricing ($0.028 per M tokens)
DeepSeek V4 Flash details

Choose Meta Llama 3 8B Instruct Reference for

  • Training toward a model you own
Meta Llama 3 8B Instruct Reference details

Common questions

Which is cheaper, DeepSeek V4 Flash or Meta Llama 3 8B Instruct Reference?

DeepSeek V4 Flash, on this workload shape. At list prices it is $0.14/$0.28 per million tokens in and out against $0.20/$0.20 for Meta Llama 3 8B Instruct Reference. Billed on Allocate: $0.15/$0.30 against $0.21/$0.21.

Which has the bigger context window?

DeepSeek V4 Flash: 1,048,576 tokens (1M) against 8,192 (8K) for Meta Llama 3 8B Instruct Reference.

Can I fine-tune DeepSeek V4 Flash or Meta Llama 3 8B Instruct Reference?

Both publish open weights (DeepSeek V4 Flash: Not listed; Meta Llama 3 8B Instruct Reference: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

Meta Llama 3 8B Instruct Reference vs Llama Guard 4 12BMeta Llama 3 8B Instruct Reference vs Meta Llama 3.1 8BMeta Llama 3 8B Instruct Reference vs Meta Llama 3 8B InstructMeta Llama 3 8B Instruct Reference vs Meta Llama 3.1 8B Instruct TurboDeepSeek V4 Flash vs Qwen3.5 9B FP8Meta Llama 3 8B Instruct Reference vs Ministral 3 14B Instruct 2512

Run the numbers on your workload

LLM price comparisonAgent cost calculatorDeepSeek V4 FlashMeta Llama 3 8B Instruct Reference

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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