API cost decision in 10 seconds

Llama 3.1 70B Instruct vs DeepSeek V3.2 Exp

Pick DeepSeek V3.2 Exp when budget and context both matter.

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

Budget verdict

Pick DeepSeek V3.2 Exp when budget and context both matter.

On the standard 1M input plus 500K output workload, DeepSeek V3.2 Exp is estimated at $0.47 vs $0.6 for Llama 3.1 70B Instruct, saving $0.13 (20.8% lower).

Cost-first pickDeepSeek V3.2 Exp
Context-first pickDeepSeek V3.2 Exp
Sample savings$0.1320.8%
10x traffic gap$1.25

DeepSeek V3.2 Exp is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.25. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

DeepSeek V3.2 Exp stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLlama 3.1 70B InstructDeepSeek V3.2 Exp
Input-heavy / RAG5M input + 500K outputDeepSeek V3.2 Exp$2.2$1.56
Balanced workload1M input + 1M outputDeepSeek V3.2 Exp$0.8$0.68
Output-heavy chatbot1M input + 5M outputDeepSeek V3.2 Exp$2.4$2.32
Cheaper input DeepSeek V3.2 Exp $0.4 vs $0.27 / 1M

DeepSeek V3.2 Exp is $0.13 cheaper per 1M input tokens (32.5% lower; 1.48x difference).

Cheaper output Llama 3.1 70B Instruct $0.4 vs $0.41 / 1M

Llama 3.1 70B Instruct is $0.01 cheaper per 1M output tokens (2.4% lower; 1.02x difference).

Larger context DeepSeek V3.2 Exp 131.07K vs 163.84K

DeepSeek V3.2 Exp has 32.77K more context (1.25x larger).

Sample workload DeepSeek V3.2 Exp $0.6 vs $0.47

DeepSeek V3.2 Exp is $0.13 cheaper on the standard workload (20.8% 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
DeepSeek V3.2 Exp 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

DeepSeek V3.2 Exp has the lower input price; Llama 3.1 70B Instruct has the lower output price; DeepSeek V3.2 Exp offers the larger context window. For the 1M input plus 500K output sample, DeepSeek V3.2 Exp 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 $0.47 for DeepSeek V3.2 Exp.

Best Fit

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

Choose DeepSeek V3.2 Exp when you care most about lower input-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, DeepSeek V3.2 Exp is estimated at $0.47 vs $0.6 for Llama 3.1 70B Instruct, saving $0.13 (20.8% lower).
  • DeepSeek V3.2 Exp is $0.13 cheaper on the standard workload (20.8% lower).
  • DeepSeek V3.2 Exp is $0.13 cheaper per 1M input tokens (32.5% lower; 1.48x difference).
  • Llama 3.1 70B Instruct is $0.01 cheaper per 1M output tokens (2.4% lower; 1.02x difference).
  • DeepSeek V3.2 Exp has 32.77K more context (1.25x larger).
Head-to-Head Specs
FeatureLlama 3.1 70B Instruct
(Meta)
DeepSeek V3.2 Exp
(DeepSeek)
Input Price
prompt tokens per 1M
$0.4$0.27
Completion Price
per 1M tokens
$0.4$0.41
Sample Workload Cost
1M input + 500K output
$0.6$0.47
Context Window131.07K163.84K
Release Date
Popularity#87#98

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionDeepSeek V3.2 ExpOn the standard 1M input plus 500K output workload, DeepSeek V3.2 Exp is estimated at $0.47 vs $0.6 for Llama 3.1 70B Instruct, saving $0.13 (20.8% lower).
High-volume input processingDeepSeek V3.2 ExpLower 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 workDeepSeek V3.2 ExpA 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...

DeepSeek V3.2 Exp

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...