API cost decision in 10 seconds

DeepSeek V3.1 vs Llama 3.1 70B Instruct

Pick Llama 3.1 70B Instruct for lower cost; pick DeepSeek V3.1 only if the larger context window matters more.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T20:08:05Z 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 DeepSeek V3.1 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 $0.6 for DeepSeek V3.1, saving $0.005 (0.8% lower).

Cost-first pickLlama 3.1 70B Instruct

Context-first pickDeepSeek V3.1

Sample savings$0.0050.8%

10x traffic gap$0.05

DeepSeek V3.1 has more context, but Llama 3.1 70B Instruct saves $0.005 on the standard workload. At 10x that traffic, the same price gap is about $0.05. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors DeepSeek V3.1, balanced workload favors Llama 3.1 70B Instruct, and output-heavy chatbot favors Llama 3.1 70B Instruct.

Workload shape	Token mix	Better pick	DeepSeek V3.1	Llama 3.1 70B Instruct
Input-heavy / RAG	5M input + 500K output	DeepSeek V3.1	$1.45	$2.2
Balanced workload	1M input + 1M output	Llama 3.1 70B Instruct	$1	$0.8
Output-heavy chatbot	1M input + 5M output	Llama 3.1 70B Instruct	$4.16	$2.4

Cheaper input DeepSeek V3.1 $0.21 vs $0.4 / 1M

DeepSeek V3.1 is $0.19 cheaper per 1M input tokens (47.5% lower; 1.9x difference).

Cheaper output Llama 3.1 70B Instruct $0.79 vs $0.4 / 1M

Llama 3.1 70B Instruct is $0.39 cheaper per 1M output tokens (49.4% lower; 1.98x difference).

Larger context DeepSeek V3.1 163.84K vs 131.07K

DeepSeek V3.1 has 32.77K more context (1.25x larger).

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

Llama 3.1 70B Instruct is $0.005 cheaper on the standard workload (0.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

DeepSeek V3.1 Calculating… Estimated API cost

Llama 3.1 70B Instruct 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 V3.1 has the lower input price; Llama 3.1 70B Instruct has the lower output price; DeepSeek V3.1 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 DeepSeek V3.1 and $0.6 for Llama 3.1 70B Instruct.

Best Fit

Choose DeepSeek V3.1 when you care most about lower input-token price, and larger context window.

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

Decision Notes

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $0.6 for DeepSeek V3.1, saving $0.005 (0.8% lower).
Llama 3.1 70B Instruct is $0.005 cheaper on the standard workload (0.8% lower).
DeepSeek V3.1 is $0.19 cheaper per 1M input tokens (47.5% lower; 1.9x difference).
Llama 3.1 70B Instruct is $0.39 cheaper per 1M output tokens (49.4% lower; 1.98x difference).
DeepSeek V3.1 has 32.77K more context (1.25x larger).

Head-to-Head Specs

Feature	DeepSeek V3.1 (DeepSeek)	Llama 3.1 70B Instruct (Meta)
Input Price prompt tokens per 1M	$0.21	$0.4
Completion Price per 1M tokens	$0.79	$0.4
Sample Workload Cost 1M input + 500K output	$0.6	$0.6
Context Window	163.84K	131.07K
Release Date	2025-08-21	2024-07-23
Popularity	#59	#87

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Llama 3.1 70B Instruct	On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $0.6 for DeepSeek V3.1, saving $0.005 (0.8% lower).
High-volume input processing	DeepSeek V3.1	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Llama 3.1 70B Instruct	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	DeepSeek V3.1	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

DeepSeek V4 Flash (free) can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.
DeepSeek V4 Flash can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.2.
R1 Distill Qwen 32B can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.43.
DeepSeek V3.2 can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.44.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
Gemini 2.5 Flash Lite offers 1.05M context with $0.3 sample workload cost.

Popular competitors

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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DeepSeek catalog

Review all tracked DeepSeek models before deciding whether this matchup is the right shortlist.

Open DeepSeek models

Meta catalog

Check other Meta models with comparable pricing, context, or release timing.

Open Meta models

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

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...