API cost decision in 10 seconds

Llama 3.1 70B Instruct vs R1 0528

Pick Llama 3.1 70B Instruct for lower cost; pick R1 0528 only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Llama 3.1 70B Instruct for lower cost; pick R1 0528 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.57 for R1 0528, saving $0.97 (61.9% lower).

Cost-first pickLlama 3.1 70B Instruct
Context-first pickR1 0528
Sample savings$0.9761.9%
10x traffic gap$9.75

R1 0528 has more context, but Llama 3.1 70B Instruct saves $0.97 on the standard workload. At 10x that traffic, the same price gap is about $9.75. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Llama 3.1 70B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLlama 3.1 70B InstructR1 0528
Input-heavy / RAG5M input + 500K outputLlama 3.1 70B Instruct$2.2$3.58
Balanced workload1M input + 1M outputLlama 3.1 70B Instruct$0.8$2.65
Output-heavy chatbot1M input + 5M outputLlama 3.1 70B Instruct$2.4$11.25
Cheaper input Llama 3.1 70B Instruct $0.4 vs $0.5 / 1M

Llama 3.1 70B Instruct is $0.1 cheaper per 1M input tokens (20% lower; 1.25x difference).

Cheaper output Llama 3.1 70B Instruct $0.4 vs $2.15 / 1M

Llama 3.1 70B Instruct is $1.75 cheaper per 1M output tokens (81.4% lower; 5.37x difference).

Larger context R1 0528 131.07K vs 163.84K

R1 0528 has 32.77K more context (1.25x larger).

Sample workload Llama 3.1 70B Instruct $0.6 vs $1.57

Llama 3.1 70B Instruct is $0.97 cheaper on the standard workload (61.9% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Llama 3.1 70B Instruct Calculating… Estimated API cost
R1 0528 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Llama 3.1 70B Instruct has the lower input price; Llama 3.1 70B Instruct has the lower output price; R1 0528 offers the larger context window. For the 1M input plus 500K output sample, Llama 3.1 70B Instruct is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.6 for Llama 3.1 70B Instruct and $1.57 for R1 0528.

Best Fit

Choose Llama 3.1 70B Instruct when you care most about lower input-token price, and lower output-token price.

Choose R1 0528 when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.57 for R1 0528, saving $0.97 (61.9% lower).
  • Llama 3.1 70B Instruct is $0.97 cheaper on the standard workload (61.9% lower).
  • Llama 3.1 70B Instruct is $0.1 cheaper per 1M input tokens (20% lower; 1.25x difference).
  • Llama 3.1 70B Instruct is $1.75 cheaper per 1M output tokens (81.4% lower; 5.37x difference).
  • R1 0528 has 32.77K more context (1.25x larger).
Head-to-Head Specs
FeatureLlama 3.1 70B Instruct
(Meta)
R1 0528
(DeepSeek)
Input Price
prompt tokens per 1M
$0.4$0.5
Completion Price
per 1M tokens
$0.4$2.15
Sample Workload Cost
1M input + 500K output
$0.6$1.57
Context Window131.07K163.84K
Release Date
Popularity#87#106

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLlama 3.1 70B InstructOn the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $1.57 for R1 0528, saving $0.97 (61.9% lower).
High-volume input processingLlama 3.1 70B InstructLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLlama 3.1 70B InstructLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workR1 0528A larger context window leaves more room for retrieved passages, conversation history, or source files.

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Llama 3.1 70B Instruct

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...

R1 0528

May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...